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      Complement peptide C3a receptor 1 promotes optic nerve degeneration in DBA/2J mice

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          Abstract

          Background

          The risk of glaucoma increases significantly with age and exposure to elevated intraocular pressure, two factors linked with neuroinflammation. The complement cascade is a complex immune process with many bioactive end-products, including mediators of inflammation. Complement cascade activation has been shown in glaucoma patients and models of glaucoma. However, the function of complement-mediated inflammation in glaucoma is largely untested. Here, the complement peptide C3a receptor 1 was genetically disrupted in DBA/2J mice, an ocular hypertensive model of glaucoma, to test its contribution to neurodegeneration.

          Methods

          A null allele of C3ar1 was backcrossed into DBA/2J mice. Development of iris disease, ocular hypertension, optic nerve degeneration, retinal ganglion cell activity, loss of RGCs, and myeloid cell infiltration in C3ar1-deficient and sufficient DBA/2J mice were compared across multiple ages. RNA sequencing was performed on microglia from primary culture to determine global effects of C3ar1 on microglia gene expression.

          Results

          Deficiency in C3ar1 lowered the risk of degeneration in ocular hypertensive mice without affecting intraocular pressure elevation at 10.5 months of age. Differences were found in the percentage of mice affected, but not in individual characteristics of disease progression. The protective effect of C3ar1 deficiency was then overcome by additional aging and ocular hypertensive injury. Microglia and other myeloid-derived cells were the primary cells identified that express C3ar1. In the absence of C3ar1, microglial expression of genes associated with neuroinflammation and other immune functions were differentially expressed compared to WT. A network analysis of these data suggested that the IL10 signaling pathway is a major interaction partner of C3AR1 signaling in microglia.

          Conclusions

          C3AR1 was identified as a damaging neuroinflammatory factor. These data help suggest complement activation causes glaucomatous neurodegeneration through multiple mechanisms, including inflammation. Microglia and infiltrating myeloid cells expressed high levels of C3ar1 and are the primary candidates to mediate its effects. C3AR1 appeared to be a major regulator of microglia reactivity and neuroinflammatory function due to its interaction with IL10 signaling and other immune related pathways. Targeting myeloid-derived cells and C3AR1 signaling with therapies is expected to add to or improve neuroprotective therapeutic strategies.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12974-020-02011-z.

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          Most cited references67

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            HTSeq—a Python framework to work with high-throughput sequencing data

            Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability and implementation: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. Contact: sanders@fs.tum.de
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              TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

              TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat.
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                Author and article information

                Contributors
                sj2967@cumc.columbia.edu
                gareth.howell@jax.org
                Journal
                J Neuroinflammation
                J Neuroinflammation
                Journal of Neuroinflammation
                BioMed Central (London )
                1742-2094
                11 November 2020
                11 November 2020
                2020
                : 17
                : 336
                Affiliations
                [1 ]GRID grid.249880.f, ISNI 0000 0004 0374 0039, The Jackson Laboratory, ; Bar Harbor, ME USA
                [2 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Division of Eye and Vision, Department of Clinical Neuroscience, St. Erik Eye Hospital, , Karolinska Institutet, ; Stockholm, Sweden
                [3 ]Zuckerman Mind Brain Behavior Institute, New York, NY USA
                [4 ]GRID grid.429997.8, ISNI 0000 0004 1936 7531, Department of Ophthalmology, , Tufts University of Medicine, ; Boston, MA USA
                [5 ]GRID grid.239585.0, ISNI 0000 0001 2285 2675, Howard Hughes Medical Institute, Department of Ophthalmology, , Columbia University Medical Center, and Zuckerman Mind Brain Behavior Institute, ; New York, NY USA
                [6 ]GRID grid.67033.31, ISNI 0000 0000 8934 4045, Sackler School of Graduate Biomedical Sciences, , Tufts University School of Medicine, ; Boston, MA USA
                [7 ]GRID grid.21106.34, ISNI 0000000121820794, Graduate School of Biomedical Sciences and Engineering, , University of Maine, ; Orono, ME USA
                Author information
                http://orcid.org/0000-0001-6194-8397
                http://orcid.org/0000-0003-0565-6474
                Article
                2011
                10.1186/s12974-020-02011-z
                7656757
                33176797
                7ef14a22-7af0-4f63-89e5-1cd267603358
                © The Author(s) 2020

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 30 June 2020
                : 28 October 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000053, National Eye Institute;
                Award ID: EY011721
                Award ID: EY021525
                Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Neurosciences
                glaucoma,complement,anaphylatoxin,microglia,monocytes,neurodegeneration
                Neurosciences
                glaucoma, complement, anaphylatoxin, microglia, monocytes, neurodegeneration

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