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      Quantitative proteomics of acutely-isolated mouse microglia identifies novel immune Alzheimer’s disease-related proteins

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          Abstract

          Background

          Microglia are innate immune cells of the brain that perform phagocytic and inflammatory functions in disease conditions. Transcriptomic studies of acutely-isolated microglia have provided novel insights into their molecular and functional diversity in homeostatic and neurodegenerative disease states. State-of-the-art mass spectrometry methods can comprehensively characterize proteomic alterations in microglia in neurodegenerative disorders, potentially providing novel functionally relevant molecular insights that are not provided by transcriptomics. However, comprehensive proteomic profiling of adult primary microglia in neurodegenerative disease conditions has not been performed.

          Methods

          We performed quantitative mass spectrometry based proteomic analyses of purified CD11b + acutely-isolated microglia from adult (6 mo) mice in normal, acute neuroinflammatory (LPS-treatment) and chronic neurodegenerative states (5xFAD model of Alzheimer’s disease [AD]). Differential expression analyses were performed to characterize specific microglial proteomic changes in 5xFAD mice and identify overlap with LPS-induced pro-inflammatory changes. Our results were also contrasted with existing proteomic data from wild-type mouse microglia and from existing microglial transcriptomic data from wild-type and 5xFAD mice. Neuropathological validation studies of select proteins were performed in human AD and 5xFAD brains.

          Results

          Of 4133 proteins identified, 187 microglial proteins were differentially expressed in the 5xFAD mouse model of AD pathology, including proteins with previously known (Apoe, Clu and Htra1) as well as previously unreported relevance to AD biology (Cotl1 and Hexb). Proteins upregulated in 5xFAD microglia shared significant overlap with pro-inflammatory changes observed in LPS-treated mice. Several proteins increased in human AD brain were also upregulated by 5xFAD microglia (Aβ peptide, Apoe, Htra1, Cotl1 and Clu). Cotl1 was identified as a novel microglia-specific marker with increased expression and strong association with AD neuropathology. Apoe protein was also detected within plaque-associated microglia in which Apoe and Aβ were highly co-localized, suggesting a role for Apoe in phagocytic clearance of Aβ.

          Conclusions

          We report a comprehensive proteomic study of adult mouse microglia derived from acute neuroinflammation and AD models, representing a valuable resource to the neuroscience research community. We highlight shared and unique microglial proteomic changes in acute neuroinflammation aging and AD mouse models and identify novel roles for microglial proteins in human neurodegeneration.

          Electronic supplementary material

          The online version of this article (10.1186/s13024-018-0266-4) contains supplementary material, which is available to authorized users.

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          Most cited references33

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          Quantitative proteomics reveals the function of unconventional ubiquitin chains in proteasomal degradation.

          All seven lysine residues in ubiquitin contribute to the synthesis of polyubiquitin chains on protein substrates. Whereas K48-linked chains are well established as mediators of proteasomal degradation, and K63-linked chains act in nonproteolytic events, the roles of unconventional polyubiquitin chains linked through K6, K11, K27, K29, or K33 are not well understood. Here, we report that the unconventional linkages are abundant in vivo and that all non-K63 linkages may target proteins for degradation. Ubiquitin with K48 as the single lysine cannot support yeast viability, and different linkages have partially redundant functions. By profiling both the entire yeast proteome and ubiquitinated proteins in wild-type and ubiquitin K11R mutant strains using mass spectrometry, we identified K11 linkage-specific substrates, including Ubc6, a ubiquitin-conjugating enzyme involved in endoplasmic reticulum-associated degradation (ERAD). Ubc6 primarily synthesizes K11-linked chains, and K11 linkages function in the ERAD pathway. Thus, unconventional polyubiquitin chains are critical for ubiquitin-proteasome system function.
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            A “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards*

            Absolute protein quantification using mass spectrometry (MS)-based proteomics delivers protein concentrations or copy numbers per cell. Existing methodologies typically require a combination of isotope-labeled spike-in references, cell counting, and protein concentration measurements. Here we present a novel method that delivers similar quantitative results directly from deep eukaryotic proteome datasets without any additional experimental steps. We show that the MS signal of histones can be used as a “proteomic ruler” because it is proportional to the amount of DNA in the sample, which in turn depends on the number of cells. As a result, our proteomic ruler approach adds an absolute scale to the MS readout and allows estimation of the copy numbers of individual proteins per cell. We compare our protein quantifications with values derived via the use of stable isotope labeling by amino acids in cell culture and protein epitope signature tags in a method that combines spike-in protein fragment standards with precise isotope label quantification. The proteomic ruler approach yields quantitative readouts that are in remarkably good agreement with results from the precision method. We attribute this surprising result to the fact that the proteomic ruler approach omits error-prone steps such as cell counting or protein concentration measurements. The proteomic ruler approach is readily applicable to any deep eukaryotic proteome dataset—even in retrospective analysis—and we demonstrate its usefulness with a series of mouse organ proteomes.
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              Transcriptomics technologies

              Transcriptomics technologies are the techniques used to study an organism’s transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst noncoding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. The first attempts to study the whole transcriptome began in the early 1990s, and technological advances since the late 1990s have made transcriptomics a widespread discipline. Transcriptomics has been defined by repeated technological innovations that transform the field. There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA sequencing (RNA-Seq), which uses high-throughput sequencing to capture all sequences. Measuring the expression of an organism’s genes in different tissues, conditions, or time points gives information on how genes are regulated and reveals details of an organism’s biology. It can also help to infer the functions of previously unannotated genes. Transcriptomic analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease. An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays.
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                Author and article information

                Contributors
                Srikant.rangaraju@emory.edu
                edammer@emory.edu
                saraza2@emory.edu
                tianwen.gao@emory.edu
                hxiao6@emory.edu
                rbetarb@emory.edu
                dduong@emory.edu
                james.a.webster@emory.edu
                cmhales@emory.edu
                jlah@emory.edu
                alevey@emory.edu
                ntseyfri@emory.edu
                Journal
                Mol Neurodegener
                Mol Neurodegener
                Molecular Neurodegeneration
                BioMed Central (London )
                1750-1326
                28 June 2018
                28 June 2018
                2018
                : 13
                : 34
                Affiliations
                [1 ]ISNI 0000 0001 0941 6502, GRID grid.189967.8, Department of Neurology, , Emory University, ; Atlanta, GA 30322 USA
                [2 ]ISNI 0000 0001 0941 6502, GRID grid.189967.8, Department of Biochemistry, , Emory University, ; Atlanta, GA 30322 USA
                Author information
                http://orcid.org/0000-0003-2765-1500
                Article
                266
                10.1186/s13024-018-0266-4
                6025801
                29954413
                6883eaa1-91ae-4f8b-a4e9-2306a09d356a
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 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.

                History
                : 13 March 2018
                : 18 June 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000065, National Institute of Neurological Disorders and Stroke;
                Award ID: K08-NS099474-1
                Award ID: K08-NS087121
                Award ID: P30 NS055077
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100005331, American Brain Foundation;
                Award ID: #28301
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000957, Alzheimer's Association;
                Award ID: 37102
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: P50 AG025688
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: U01AG046161
                Award ID: RF1AG057471
                Award ID: R01AG057330
                Award ID: RF1AG057470
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Neurosciences
                microglia,neurodegeneration,neuroinflammation,immunology,proteomics,mass spectrometry,alzheimer’s disease

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