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      CD8 + T cells induce interferon-responsive oligodendrocytes and microglia in white matter aging

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          Abstract

          A hallmark of nervous system aging is a decline of white matter volume and function, but the underlying mechanisms leading to white matter pathology are unknown. In the present study, we found age-related alterations of oligodendrocyte cell state with a reduction in total oligodendrocyte density in aging murine white matter. Using single-cell RNA-sequencing, we identified interferon (IFN)-responsive oligodendrocytes, which localize in proximity to CD8 + T cells in aging white matter. Absence of functional lymphocytes decreased the number of IFN-responsive oligodendrocytes and rescued oligodendrocyte loss, whereas T-cell checkpoint inhibition worsened the aging response. In addition, we identified a subpopulation of lymphocyte-dependent, IFN-responsive microglia in the vicinity of the CD8 + T cells in aging white matter. In summary, we provide evidence that CD8 + T-cell-induced, IFN-responsive oligodendrocytes and microglia are important modifiers of white matter aging.

          Abstract

          Aging is associated with the formation of focal white matter lesions and atrophy. The authors discovered a role for CD8 + T cells in driving white matter-specific interferon responses in microglia and oligodendrocytes, leading to oligodendrocyte loss.

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          Most cited references74

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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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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              STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

              Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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                Author and article information

                Contributors
                oezguen.goekce@med.uni-muenchen.de
                mikael.simons@dzne.de
                Journal
                Nat Neurosci
                Nat Neurosci
                Nature Neuroscience
                Nature Publishing Group US (New York )
                1097-6256
                1546-1726
                24 October 2022
                24 October 2022
                2022
                : 25
                : 11
                : 1446-1457
                Affiliations
                [1 ]GRID grid.411095.8, ISNI 0000 0004 0477 2585, Institute for Stroke and Dementia Research, , University Hospital of Munich, Ludwig Maximilian University (LMU) of Munich, ; Munich, Germany
                [2 ]GRID grid.6936.a, ISNI 0000000123222966, Institute of Neuronal Cell Biology, , Technical University Munich, ; Munich, Germany
                [3 ]GRID grid.424247.3, ISNI 0000 0004 0438 0426, German Center for Neurodegenerative Diseases, ; Munich, Germany
                [4 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, Graduate School of Systemic Neurosciences, LMU Munich, ; Munich, Germany
                [5 ]GRID grid.452617.3, Munich Cluster of Systems Neurology, ; Munich, Germany
                [6 ]GRID grid.411760.5, ISNI 0000 0001 1378 7891, Department of Neurology, Section of Developmental Neurobiology, , University Hospital Würzburg, ; Würzburg, Germany
                Author information
                http://orcid.org/0000-0001-5926-8608
                http://orcid.org/0000-0002-0642-1610
                http://orcid.org/0000-0001-6927-5772
                http://orcid.org/0000-0002-0500-8218
                http://orcid.org/0000-0002-7628-0163
                http://orcid.org/0000-0003-1194-5256
                http://orcid.org/0000-0001-6319-404X
                http://orcid.org/0000-0001-5329-192X
                Article
                1183
                10.1038/s41593-022-01183-6
                9630119
                36280798
                80d301e1-1981-4f2b-b823-158ba9efbeae
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 November 2021
                : 14 September 2022
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                © The Author(s), under exclusive licence to Springer Nature America, Inc. 2022

                Neurosciences
                oligodendrocyte,myelin biology and repair,neural ageing,neuroimmunology,microglia
                Neurosciences
                oligodendrocyte, myelin biology and repair, neural ageing, neuroimmunology, microglia

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