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• W2756092850 abstract "Article28 September 2017Open Access Source DataTransparent process A novel microglial subset plays a key role in myelinogenesis in developing brain Agnieszka Wlodarczyk Agnieszka Wlodarczyk Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Inge R Holtman Inge R Holtman Department of Neuroscience, Medical Physiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Martin Krueger Martin Krueger Institute for Anatomy, University of Leipzig, Leipzig, Germany Search for more papers by this author Nir Yogev Nir Yogev Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Julia Bruttger Julia Bruttger Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Reza Khorooshi Reza Khorooshi Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Anouk Benmamar-Badel Anouk Benmamar-Badel Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Department of Biology, Ecole Normale Supérieure de Lyon, University of Lyon, Lyon, France Search for more papers by this author Jelkje J de Boer-Bergsma Jelkje J de Boer-Bergsma Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Nellie A Martin Nellie A Martin Department of Neurology, Institute of Clinical Research, Odense University Hospital, Odense, Denmark Search for more papers by this author Khalad Karram Khalad Karram Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Isabella Kramer Isabella Kramer Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Erik WGM Boddeke Erik WGM Boddeke Department of Neuroscience, Medical Physiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Ari Waisman Ari Waisman orcid.org/0000-0003-4304-8234 Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Bart JL Eggen Bart JL Eggen Department of Neuroscience, Medical Physiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Trevor Owens Corresponding Author Trevor Owens [email protected] orcid.org/0000-0001-9315-6036 Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Agnieszka Wlodarczyk Agnieszka Wlodarczyk Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Inge R Holtman Inge R Holtman Department of Neuroscience, Medical Physiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Martin Krueger Martin Krueger Institute for Anatomy, University of Leipzig, Leipzig, Germany Search for more papers by this author Nir Yogev Nir Yogev Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Julia Bruttger Julia Bruttger Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Reza Khorooshi Reza Khorooshi Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Anouk Benmamar-Badel Anouk Benmamar-Badel Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Department of Biology, Ecole Normale Supérieure de Lyon, University of Lyon, Lyon, France Search for more papers by this author Jelkje J de Boer-Bergsma Jelkje J de Boer-Bergsma Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Nellie A Martin Nellie A Martin Department of Neurology, Institute of Clinical Research, Odense University Hospital, Odense, Denmark Search for more papers by this author Khalad Karram Khalad Karram Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Isabella Kramer Isabella Kramer Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Erik WGM Boddeke Erik WGM Boddeke Department of Neuroscience, Medical Physiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Ari Waisman Ari Waisman orcid.org/0000-0003-4304-8234 Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany Search for more papers by this author Bart JL Eggen Bart JL Eggen Department of Neuroscience, Medical Physiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Search for more papers by this author Trevor Owens Corresponding Author Trevor Owens [email protected] orcid.org/0000-0001-9315-6036 Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark Search for more papers by this author Author Information Agnieszka Wlodarczyk1, Inge R Holtman2, Martin Krueger3, Nir Yogev4,8, Julia Bruttger4, Reza Khorooshi1, Anouk Benmamar-Badel1,5, Jelkje J Boer-Bergsma6, Nellie A Martin7, Khalad Karram4, Isabella Kramer1, Erik WGM Boddeke2, Ari Waisman4, Bart JL Eggen2 and Trevor Owens *,1 1Department of Neurobiology Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark 2Department of Neuroscience, Medical Physiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 3Institute for Anatomy, University of Leipzig, Leipzig, Germany 4Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany 5Department of Biology, Ecole Normale Supérieure de Lyon, University of Lyon, Lyon, France 6Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 7Department of Neurology, Institute of Clinical Research, Odense University Hospital, Odense, Denmark 8Present address: Department of Neurology, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany *Corresponding author. Tel: +45 65503951; E-mail: [email protected] The EMBO Journal (2017)36:3292-3308https://doi.org/10.15252/embj.201696056 See also: ML Bennett & BA Barres (November 2017) PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Microglia are resident macrophages of the central nervous system that contribute to homeostasis and neuroinflammation. Although known to play an important role in brain development, their exact function has not been fully described. Here, we show that in contrast to healthy adult and inflammation-activated cells, neonatal microglia show a unique myelinogenic and neurogenic phenotype. A CD11c+ microglial subset that predominates in primary myelinating areas of the developing brain expresses genes for neuronal and glial survival, migration, and differentiation. These cells are the major source of insulin-like growth factor 1, and its selective depletion from CD11c+ microglia leads to impairment of primary myelination. CD11c-targeted toxin regimens induced a selective transcriptional response in neonates, distinct from adult microglia. CD11c+ microglia are also found in clusters of repopulating microglia after experimental ablation and in neuroinflammation in adult mice, but despite some similarities, they do not recapitulate neonatal microglial characteristics. We therefore identify a unique phenotype of neonatal microglia that deliver signals necessary for myelination and neurogenesis. Synopsis Transcriptome profiling of murine microglia identified a population expressing CD11c as a potent source of neurodevelopmental signals in neonatal mice. These cells are a major source of IGF1 that is necessary for myelinogenesis in the developing CNS. The transcriptome of neonatal microglia differs dramatically from that of homeostatic, immune-activated and repopulating adult microglia. A unique CD11c+ microglial subpopulation with a neurosupportive gene signature greatly expands during postnatal neurodevelopment. Selective deletion of Igf1 from CD11c+ microglia leads to reduction of brain weight and significant impairment in primary myelination. Introduction Microglia are resident myeloid cells of the central nervous system (CNS) that originate from yolk sac precursors and colonize the brain very early during embryonic life (Ginhoux et al, 2010; Schulz et al, 2012; Kierdorf et al, 2013). They are autonomously maintained through proliferation (Askew et al, 2017) and are not replaced from blood-derived precursors during the lifetime of the host, at least under normal circumstances (reviewed in Ginhoux et al, 2013; Prinz & Priller, 2014). The role of microglia has traditionally been studied in the context of immune responses in the diseased CNS, and they have been implicated in neuroinflammatory and neurodegenerative diseases. Although their importance in homeostasis and brain development is recognized (Biber et al, 2014; Matcovitch-Natan et al, 2016), their exact role in these processes remains incompletely defined. Evidence supporting the view that microglia are crucial players in neurodevelopment includes that mice lacking the CSF1R receptor for CSF1 or IL34, which is critical for microglia maintenance, show abnormal brain development (Elmore et al, 2014). Moreover, they are involved in synaptic pruning (Paolicelli et al, 2011; Schafer et al, 2012; Kettenmann et al, 2013; Zhan et al, 2014), they modulate axonal outgrowth and cortical interneuron positioning (Squarzoni et al, 2014), and they support survival of layer V cortical neurons during postnatal development by producing neuroprotective insulin-like growth factor 1 (IGF1) (Ueno et al, 2013). IGF1 has also been shown to be essential for primary myelination, but the microglial contribution to this process is relatively unstudied. In many neuroinflammatory (Wlodarczyk et al, 2014, 2015) and degenerative (Butovsky et al, 2006) conditions, a normally rare subpopulation of microglia that expresses the integrin complement receptor CD11c increases in proportion and number. We have previously shown in an animal model for multiple sclerosis, experimental autoimmune encephalomyelitis (EAE), that while CD11c+ microglia are effective antigen-presenting cells for T-cell proliferation, they are a poor source of pro-inflammatory cytokines (Wlodarczyk et al, 2014) and that they differ from infiltrating DC and CD11c− microglia with respect to expression of many genes (Wlodarczyk et al, 2015). Interestingly, we showed that CD11c+ microglia uniquely express Igf1 during EAE (Wlodarczyk et al, 2015), suggesting that they may be neuroprotective. Here, we show that neonatal microglia differ dramatically in their gene expression profile from microglia in healthy adults and mice with EAE, showing a neurogenic signature. CD11c+ microglia greatly expand during postnatal development (PN3-5) and then dramatically contract as mice age to adulthood. They express a characteristic neurosupportive gene profile, equipping them to play a fundamental role in the developing CNS. Moreover, they are appropriately located for delivery of signals necessary for neuronal development and primary myelination. Importantly, we show that Igf1 deficiency in CD11c+ microglia leads to an impairment in primary myelination. Three separate CD11c-targeted toxin regimens all resulted in a similar selective transcriptional outcome in neonatal mice, with a response distinct from that of adult microglia. Furthermore, whereas CD11c+ microglia are among the cells that repopulate the adult brain after microglial ablation, they do not show myelinogenic or neurogenic signatures. Thus, we identify neonatal microglia, and especially the CD11c+ subset, as key tissue macrophages for CNS development. Results CD11c+ microglia emerge during postnatal development During neuroinflammation, CD11c+ microglia are the major source of Igf1 (Wlodarczyk et al, 2015), a gene critical for neurodevelopment, myelination, and neurogenesis. Thus, we asked whether this microglial subset is present during postnatal development. Mononuclear cells were isolated from perfused brains from PN2, PN3, PN7, PN28, and adult (8–12 weeks old) B6 and CCR2rfp/+ mice and analyzed by flow cytometry for CD11c expression. Microglia are defined by a lower level of cell surface CD45 than blood-derived leukocytes, expression of fractalkine receptor CX3CR1, and lack of CCR2 chemokine receptor (Mizutani et al, 2012). We used relative CD45 levels (Remington et al, 2007) and CCR2 expression to discriminate between blood-derived leukocytes (CD45high CCR2+) and resident microglia (CD45dimCCR2−). There were very few CD45high CD11c+ cells (0.2% live gate) in brain isolates at indicated time points. Nevertheless, nearly 85% of them were CCR2-positive (Fig 1A). In contrast, more than 99% of CD45dim CD11b+ CD11c+ cells (microglia) were CCR2-negative (Fig 1A). The proportion of CD11c+ microglia, as a percentage of total microglia, increased significantly from PN2 (12%) to PN3 (17%) and then sharply decreased by PN7 (8%), falling to < 3% in young (PN28) and adult animals (Fig 1B). Absolute numbers of CD11c+ microglia significantly increased from PN2 to PN3-5. After PN5, the numbers of CD11c+ microglia dramatically decreased, reaching only 50 and 10% of PN3-5 levels at PN7 and PN28, respectively (Fig 1C). Numbers of CD11c– microglia were also elevated in neonatal CNS, increasing from PN2 to PN3. However, unlike CD11c+ microglia, their numbers were stable from PN3 throughout adulthood (Fig 1D). Immunofluorescent stainings of perfused PN4-5 B6 and CX3CR1GFP/+ murine brains showed that CD11c+ microglia cells were not homogenously distributed throughout the brain, but localized mainly in the corpus callosum and cerebellar white matter, in contrast to other areas of the brain where they were virtually absent (Fig 1E–G). All of the CD11c-positive cells co-stained with the microglial marker IBA1 (Fig 1H) and co-localized with CX3CR1 (Fig 1I). Importantly, laminin staining revealed that they were localized in the brain parenchyma and not in blood vessels or in the perivascular space (Fig 1J). Figure 1. CD11c+ microglia emerge during postnatal neurodevelopment A. Representative flow cytometry profiles of five individual brain suspensions prepared from PN5 mice showing RFP expression driven by Ccr2 promoter on CD45highCD11c+ cells (R1) and lack of expression on CD45lowCD11c+ microglia (R2). B–D. Flow cytometry analysis showing CD11c+ microglia presented as a percentage from total microglia (B), absolute numbers of CD11c+ microglia (C), and CD11c− microglia (D) at different time points PN2 (n = 4), PN3 (n = 6), PN5 (n = 6), PN7 (n = 6), PN28 (n = 9), and adult mouse brain (n = 16). E. Representative low-power micrographs showing patches of CD11c-stained cells (red) co-localizing with GFP driven by Cx3cr1 promoter (green) in corpus callosum (cc) and single CX3CR1-positive cells in cortex (ctx) and hippocampus (hp) in PN4-5 brains (n = 3). Scale bar = 200 μm. F–I. Representative confocal microscopic micrographs showing CD11c-stained cells (red) in corpus callosum (F) and cerebellum (G) as well as co-localization of CD11c marker (red) and IBA1 (green) (H) or CX3CR1 (green) (I) in PN4-5 brains (n = 3). Scale bars = 15 μm. J. Confocal microscopic analysis of two individual brains showing CD11c (red), CX3CR1 (green) double-positive cells localized in the parenchyma, outside of the laminin-stained blood vessels (blue) (n = 2). Scale bar = 15 μm. Data information: Data are based on three experimental repeats. Data are presented as means ± SEM; each n represents an individual mouse. P-values were determined by two-tailed Mann-Whitney U-test. ns, not significant; *P < 0.05; **P < 0.01. Download figure Download PowerPoint Neonatal CD11c+ microglia are a critical source of IGF1 for primary myelination Next, we were interested whether CD11c+ microglia, so abundant in areas of primary myelination, are a source of Igf1 that is critical for this process. We compared levels of Igf1 expression in MACS-sorted neurons, astrocytes, oligodendrocyte precursor cells (OPCs), and CD11b+ cells (which include mostly microglia) from unperfused PN4-7 brains. Although all cell populations expressed detectable levels of Igf1, CD11b+ cells showed at least eightfold higher expression of this gene (Fig 2A). Igf1 transcripts were further compared in CD11c+ and CD11c− microglial populations. CD11c+ microglia expressed significantly higher levels of Igf1 (sevenfold) than their CD11c− counterparts (Fig 2B). Figure 2. Neonatal CD11c+ microglia are a major source of myelinogenic Igf1 A, B. Expression of Igf1 relative to 18S rRNA in MACS-sorted microglia, OPC, astrocytes and neurons (n = 4) (A) as well as FACS-sorted CD11c+ and CD11c− microglia (n = 6) (B) from brains of PN4-7 mice. C. Representative micrographs showing patches of Cre-GFP, CD11b double-positive cells in corpus callosum from PN4-5 CD11c Cre-GFP Igf1fl/fl brains (n = 3), Scale bar = 50 μm. D. Genomic PCR analysis of Cre recombination in MACS-sorted splenic dendritic cells (DC) from Igf1wt/fl and microglia, OPC, astrocytes, and neurons from CD11cCre-GFP Igf1fl/fl. Wild-type Igf1 gene is detected as an ˜1-kb band; Cre-induced recombination is detected as an ˜0.2-kb band, while the Igf1/flox locus cannot be amplified under the assay condition (Liu et al, 1998). E. Expression of Igf1 relative to 18S rRNA in FACS-sorted splenic CD11c+ cells (n = 5), CD11c+ microglia (n = 5), and CD11c− microglia (n = 5) from Igf1fl/fl mice and Cre+ microglia (n = 4, each n represents a pool of 2 brains) from CD11cCre-GFP Igf1fl/fl mice. F. Bar graph showing weights of brains from PN21 Igf1fl/fl (blue) (n = 8) and CD11cCre-GFP Igf1fl/fl (red) (n = 4) mice. G. Expression of Igf1, Mog, Plp, and Mbp relative to 18S rRNA in brain tissue from PN21 CD11cCre-GFP Igf1fl/fl and Igf1fl/fl mice (F) n = 6. H, I. Representative micrographs (H) and quantification of PLP staining intensity (I) in corpus callosum of CD11cCre-GFP Igf1fl/fl (red) (n = 4) and Igf1fl/fl (blue) (n = 6) PN21 brains. J–M. Representative electron microscopy micrographs (J), mean G-ratios (K), and distribution of G-ratios (L, M) in corpus callosum from Igf1fl/fl (blue) (n = 8) and CD11c CD11cCre-GFP Igf1fl/fl (red) (n = 6) PN21 brains. Scale bar = 1 μm. Data information: Data are based on at least two experimental repeats. Data are presented as means ± SEM; each n represents an individual mouse. P-values were determined by two-tailed Mann-Whitney U-test (A, B, E, G, I), Welch's t-test (F, K, M) (distribution was normal) or two-way ANOVA with Sidak's multiple comparisons test (L) (variances were similar, and distribution was normal); ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001. Source data are available online for this figure. Source Data for Figure 2 [embj201696056-sup-0003-SDataFig2.jpg] Download figure Download PowerPoint To confirm the importance of CD11c+ microglia-derived IGF1 on primary myelination, we used a CD11c-Cre-GFP driver to delete the Igf1 gene specifically in CD11c+ cells. In line with data presented in Fig 1, Cre-GFP positive cells were localized mainly in corpus callosum (Fig 2C) and cerebellum. We confirmed that all of these cells co-stained with CD11b (Fig 2C). PCR analysis of genomic DNA in sorted OPC, astrocytes, neurons, and microglia from CD11cCre-GFP Igf1fl/fl PN7 mice revealed Cre-induced recombination only in microglia (Fig 2D). We additionally showed lack of recombination in astrocytes from PN21 CD11cCre-GFP Igf1fl/fl mice, and we showed recombination in microglia but not in neurons, OPC, or astrocytes from PN7 CD11cCre-GFP Igf1fl/WT heterozygous mice (Fig EV1). This is in line with results from Goldmann et al (2013), who showed that in a CD11cCre: Rosa EYFP reporter mouse EYFP was exclusively expressed by Iba1 + microglia in CNS parenchyma and that there was no ectopic expression outside the myeloid lineage in these mice. Flow cytometry analysis showed that CD11c+ but not CD11c− microglia or CD45 negative cells were Cre-GFP positive (not shown). Igf1 expression was significantly reduced in sorted Cre+ CD11c+ microglia, reaching levels of CD11c− microglia and splenic CD11c+ cells (Fig 2E). Even though the efficiency of Cre recombination in CD11c+ microglia was only close to 40% (Fig 2D), we observed lower brain weight (Fig 2F), significant decrease in Igf1, Plp, Mag, and Mbp, and slight downregulation of Mog gene expression (Fig 2G) in PN21 CD11cCre-GFP Igf1fl/fl brains in comparison with Igf1-intact Igf1fl/fl littermate controls. This was accompanied by less intense PLP staining (Fig 2H) and significantly higher myelin G-ratio (Fig 2I–K) in corpus callosum. Conversely, we observed higher representation of less myelinated fibers (G-ratio 0.8–0.85) and significantly less frequent sufficiently myelinated axons (G-ratio = 0.65–0.7) in corpus callosum of CD11cCre-GFP Igf1fl/fl than in littermate controls (Fig 2L and M). Altogether, our data point to an important role for IGF1-producing CD11c+ microglia in primary myelination. Click here to expand this figure. Figure EV1. Cre recombination in microgliaGenomic PCR analysis of Cre recombination in MACS-sorted splenic dendritic cells (DC) from PN21 Igf1wt/fl; DC, astrocytes from PN21 CD11cCre-GFP Igf1fl/fl (homozygous) as well as microglia, neurons, OPC, and astrocytes from CD11cCre-GFP Igf1wt/fl (heterozygous). Wild-type Igf1 gene is detected as an ~1-kb band; Cre-induced recombination is detected as an ~0.2-kb band, while the Igf1/flox locus cannot be amplified under the assay condition (Liu et al, 1998). Download figure Download PowerPoint Distinct gene signatures in microglia subsets during development and EAE We have previously shown that numbers and proportions of CD11c+ microglia dramatically increase during EAE, and the data suggested that they might play a protective role during the disease (Wlodarczyk et al, 2014, 2015). To assess whether microglial subsets from developing CNS and mice with symptomatic EAE are similar, we compared transcriptomes of sorted CD11c+ and CD11c− microglia from PN4-6 CNS and symptomatic EAE (grades 3-5) as well as of total naïve adult microglia (Dataset EV1). Microglial markers (Aif1, Itgam, Cx3cr1, Csf1r) and signature genes (Butovsky et al, 2014; Bennett et al, 2016) (Spi1, Irf8, Olfml3, Hexb, Fcrls, Tgfbr1, P2ry12, Siglech, Tmem119) were similarly expressed in both CD11c+ and CD11c− neonatal and EAE microglia populations as in adult microglia (not shown). CD11c+ microglia from neonates and mice with EAE strongly upregulated Itgax expression, confirming high purity of sorted cells and validating the RNA-seq assay (not shown). Moreover, we identified 20 genes (Itgax, Gpnmb, Spp1, Igf1, Colec12, Ccl5, Ak4, Lox, Mmp12, Cpeb1, Ntn1, Clec7a, Saa3, Ahnak2, Fabp5, Hpse, Gm26902, Cspg4, Fam20c, and Stra6 l) that were associated with the CD11c+ microglia population. A multidimensional scaling (MDS) plot showed that neonatal, naïve adult microglia, and microglia from EAE formed three separate and distinct global gene expression clusters, while CD11c-positive and negative subpopulations clustered relatively close together for each condition (Fig 3A). The major difference was therefore related to developmental age rather than subset phenotype. Figure 3. Transcriptome analysis of neonatal, EAE, and adult microglia A. Multidimensional scaling shows that neonatal, EAE subpopulations of microglia and adult microglia have distinct transcriptional profiles. Colors indicate six different groups of samples: orange represents neonatal CD11c+ microglia (n = 4), green neonatal CD11c− microglia (n = 4), blue EAE CD11c+ microglia (n = 3), purple EAE CD11c− microglia (n = 3), and black adult microglia (n = 3). Each n represents a pool of 10–15 mice from five individual EAE immunizations and four individual cell sorts of neonatal and naïve adult microglia. B, C. Co-expression networks were generated for 12,691 genes of the transcriptome dataset. Average linkage hierarchical clustering was applied to the topological overlap matrix and branches of highly correlating genes were formed, which were cut and assigned a color (B). For each module, the Module Eigengene (ME) was calculated, which represents the expression profile of the module. The ME values were correlated with binary variables (Spearman's correlation) that represent control, CD11c+, EAE, neonatal, and CD11c+ microglia in neonates and EAE. Within each table cell, upper values represent correlation coefficients between ME and the variable, while lower values in brackets correspond to Student asymptotic P-value (C). D. A boxplot containing the distribution of the black, blue, brown, and green ME values across the samples. The boxes contain the first and third quartiles; center line indicates the median and whiskers indicate minimum and maximum values. Kruskal–Wallis test was applied to determine whether ME values were significantly different between the groups. E. Table showing number of genes within the module and the top GO term for each module with Benjamini-corrected P-value. Download figure Download PowerPoint In order to identify gene expression profiles associated with microglia from the different conditions, weighted gene co-expression network analysis (WGCNA) was applied to the RNA-seq data. In WGCNA, genes are clustered according to co-expression and a network with seven co-expression modules was identified (Fig 3B). From each module, the Module Eigengene (ME) was calculated, which is the first principal component and functions as a representative of the module. The ME values were correlated with variables that represent control adult microglia (“control”), CD11c+ microglia population (“CD11c”), EAE microglia populations (“EAE”), neonatal microglia populations (“neonatal”), and CD11c+ microglia from EAE (“EAE CD11c+”) and neonates (“neonatal CD11c+”) (Fig 3C) are depicted as a box plot per condition (Fig 3D). With the exception of the gray module (that contained unclustered genes), all modules correlated significantly (P < 0.005) with some of the indicated variables. The ME of the yellow module was negatively correlated with “control” (−0.93; downregulated) and positively with “neonatal” (between 0.068 and 0.65). The top gene ontology (GO) enrichment category associated with the yellow module was the “cell cycle” term (Fig 3E). This suggested that microglia from neonates more abundantly expressed cell cycle genes, which is in line with the observed microglia proliferation during neurodevelopment (Matcovitch-Natan et al, 2016). In contrast, the turquoise module was negatively correlated with “neonatal” variable (−0.84) and positively correlated with “control” (0.76). This module was enriched for GO term “regulation of cellular metabolic process”. The red module was not only negatively correlated with the “control”, but also positively correlated with the “CD11c” variable (−0.73 versus 0.78). This suggested an activation-related increase in expression, which is more pronounced in CD11c-positive microglia. This red module was enriched for a “translation” GO term (Fig 3E), suggesting that neonatal and EAE microglia and in particular CD11c microglia were more translationally active. Interestingly, four modules (black, blue, green, and brown) showed clear opposite correlations with the “EAE” and “neonatal” variables (Fig 3C). Where the blue and black modules increased their expression in EAE microglia, the expression of these modules was reduced in neonatal microglia (Fig 3D). The blue and black modules were enriched for “immune system process” and “immune response” categories. In contrast, ME values of the brown and green modules negatively correlated (Fig 3C) and were decreased (Fig 3D) in EAE microglia and positively correlated (Fig 3C) and increased (Fig 3D) in neonatal microglia. The green and brown modules were enriched for “nervous system development” and “localization” GO terms, respectively (Fig 3E). Additionally, the brown module also significantly correlated with the CD11" @default.
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• W2756092850 title "A novel microglial subset plays a key role in myelinogenesis in developing brain" @default.
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• W2756092850 doi "https://doi.org/10.15252/embj.201696056" @default.
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