The microglial sensome revealed by direct RNA sequencing - PubMed (original) (raw)

. 2013 Dec;16(12):1896-905.

doi: 10.1038/nn.3554. Epub 2013 Oct 27.

Affiliations

The microglial sensome revealed by direct RNA sequencing

Suzanne E Hickman et al. Nat Neurosci. 2013 Dec.

Abstract

Microglia, the principal neuroimmune sentinels of the brain, continuously sense changes in their environment and respond to invading pathogens, toxins and cellular debris. Microglia exhibit plasticity and can assume neurotoxic or neuroprotective priming states that determine their responses to danger. We used direct RNA sequencing, without amplification or cDNA synthesis, to determine the quantitative transcriptomes of microglia of healthy adult and aged mice. We validated our findings using fluorescence dual in situ hybridization, unbiased proteomic analysis and quantitative PCR. We found that microglia have a distinct transcriptomic signature and express a unique cluster of transcripts encoding proteins for sensing endogenous ligands and microbes that we refer to as the sensome. With aging, sensome transcripts for endogenous ligand recognition were downregulated, whereas those involved in microbe recognition and host defense were upregulated. In addition, aging was associated with an overall increase in the expression of microglial genes involved in neuroprotection.

PubMed Disclaimer

Figures

Figure 1

Figure 1. The microglial Sensome identified by direct RNA sequencing

Of the 21025 transcripts measured, we used gene ontology (GO) analysis and identified 1299 potential sensome genes. Of these, we selected the top 100 transcripts with the highest enrichment of microglia/brain and termed this gene collection as the microglial “Sensome”. a–b. Expression levels of genes of the microglial Sensome in mRNA copies per million reads (CMMR) in microglia and brain. Values are mean ± SD of three different experiments done with microglia pooled from 22, 10 and 20 mice, respectively. and three pools of RNA from 2 brains each. For differences in expression between microglia and brain p<0.00001 for all Sensome genes shown in graph. Data can be found in Supplementary Table 1. c. Log2Fold change (graybars) of non-microglial genes specific for neurons, astrocytes and oligodendrocytes and show “derichment” in microglia compared to whole brain. d. Network analysis of the microglial Sensome by STRING identified a DAP12 centered pathway with 44/100 genes with direct or indirect interaction with DAP12. Of these, 24 have a direct interaction with Dap12 and are highlighted using a largerfont.

Figure 2

Figure 2. Differences between microglia and macrophages revealed by DRS

a. Venn diagram showing similarities and differences of the top 10% of transcripts expressed in microglia and macrophages. b. Heat map and hierarchal clustering of the transcripts that are unique to microglia or macrophages, showing a distinct signature for each of the cell types. c. The top 25 transcripts with the highest CMMR that are unique to microglia have barely detectable levels in macrophages (p<0.00001 for differences between microglia and macrophage expression). These top 25 transcripts show high level of enrichment (Log2Fold Change >4) over macrophages regardless of the level of expression in microglia. d. The top 25 transcripts unique to macrophages with the highest CMMR have barely detectable levels in microglia (p<0.00001 for differences between macrophages and microglia expression). These top 25 transcripts unique to macrophages show high level of enrichment (Log2Fold Change >5) over microglia regardless of the level of expression in macrophages. (Values in c–d mean ± SD of three different experiments done with microgliapooled from 22, 10and 20 mice, respectively and three pools of macrophages from 10 mice per pool) Data for Figure 1c–d can be found in Supplementary Table 2.

Figure 3

Figure 3. Comparative expression of the microglial and macrophages genes

Comparison ofexpression levels of Sensome genes and those involved in regulating the immune response reveal a distinct immune signature for each cell type. a, b. Expression levels of the microglial Sensome in microglia and macrophages show that several genes are differentially expressed. c. Purinergic P2rx receptors. d. Purinergic P2ry receptors. e. Chemokine Ccr and Cx3cr1 receptors. f. Chemokine Cxcr receptors. g. Fc receptors. h. Interferon-inducible transmembrane (Ifitms). i. Toll-like receptors (Tlrs) 1–13. j. Sialic acid binding immunoglobulin lectins (Siglecs). (Values are mean ± SD of three different experiments done with microglia pooled from 22, 10 and 20 mice, respectively and three pools of macrophages from 10 mice per pool.) Data for Figure 3a–j can be found in Supplementary Table 2.

Figure 4

Figure 4. RNAscope dual fluorescent in situ hybridization

Dual RNAscope was performed on brain slices from adult mice for CD11b and sensome genes with high (P2ry12), intermediate (Cx3cr1) and low (P2ry6) levels of expression and for the highly expressed Hexb gene. The results confirm DRS findings and show exclusive expression in microglia and no expression in CD11b negative cells. a. Dual RNAscope for CD11b (red) and P2ry12 (green) probes, nuclei are stained with DAPI (blue). Bottom panels are magnified images of the double positive cells shown in the top panel. b. Dual RNAscope for CD11b (red) and Cx3cr1 (green) probes. Bottom panels are magnified images of the double positive cells shown in the top panel. c. Dual RNAscope for CD11b (red) and P2ry6 (green) probes. Bottom panels are magnified images of the double positive cells shown in the top panel. d. Quantitative image analysis of RNAscope data for _CD11b_+ cells with P2ry12 and Cx3cr1 and P2ry6. e. Dual RNAscope for CD11b (red) and Hexb (green) probes in the cortex, hippocampus and cerebellum. f. Nearly all of _CD11b_+ cells in the cortex, hippocampus and cerebellum, respectively, co-express HexB.

Figure 5

Figure 5. Proteomic analysis of microglia and macrophages

a. Fluorescent 2D-DIGE of microglia (labeled in red) and macrophages (labeled in green) proteins showing common (labeled in yellow) and unique proteins for each cell type. Right panel shows an enlarged view of the area delineated in left panel. b. quantitative diagram of spot # 10 identified by mass spectrometry as Padi4 showing lower level of expression in microglia compared to macrophages. c. quantitative diagram of spot # 27 identified by mass spectrometry as fascin showing higher level of expression in microglia compared to macrophages. d, e. Comparison of protein levels (measured by mass spectrometry) and mRNA levels (measured by DRS) of Padi4 and fascin in macrophages and microglia. (DRS values are mean ± SD of three different experiments done with microglia pooled from 22, 10 and 20 mice, and from three pools of macrophages from 10 mice per pool, protein values are from pooled microglia and macrophages isolated from 70 and 50 mice, respectively). f. Validation by qPCR of some genes obtained with DRS on new cohorts of mice. The new cohorts comprised 5 sorted microglia pools and 6 macrophage pools from sorting of six sets using five mice per set. Ratio values for qPCR and DRS data represent the ratio of gene of interest to B2-micoglobulin expression. Data are plotted as log2 fold differencebetween microglia/macrophageratio values.

Figure 6

Figure 6. Effects of Aging on the microglial mRNA expression profile

a. Heatmap of the 10598 microglial transcripts expressed at >1CMMR shows that 1831 transcripts were upregulated, 1672 were downregulated and 7095 remained unchanged with aging. b. GSEA pathways analysis showed upregulation of potentially neuroprotective pathways such as Stat 3 and Neuregulin-1 and downregulation of potentially neurotoxic pathways such as oxidative phosphorylation. Each bar at the bottom of each panel represents a member gene of the respective pathway and shows its relative location in the ranked list of genes (lowest panel).

Figure 7

Figure 7. Upregulation of alternative priming genes in microglia from aged mice

a,b. Alternative and classical priming genes in microglia from 24 months compared with mice 5 months of age old mice show a wide range of expression levels. a. In old mice, 24 of 37 alternative priming state markers were statistically significantly upregulated (*p<0.016). b. In 24 months old vs. microglia from 5 months old mice, 5 of 12 markers of the classical priming state were significantly upregulated in microglia, while the remaining 7 were down-regulated or not significantly changed. c. Analysis of 22 inflammasome-associated genes shows that 4 are significantly up-regulated in old mice compared with young ones (*p<0.025), while the remaining 18 genes are down-regulated or not significantly changed. Taken together the data suggest a trend toward increased expression of genes involved in resolution of inflammation and neuroprotection. Values are Log2 Fold change of three different experiments done with microglia pooled from 22, 10 and 20 young mice, respectively and from three pools of 10 mice per pool from old mice.. Data for this figure is found in Supplemental Table 3.

Figure 8

Figure 8. The microglial sensome in aging

a. measurement of the Log2Fold change of genes encoding the microglial sensome as determined by DRS show that ~81% of the genes are significantly downregulated (Escr1_→_Tmem173, p<0.043) and encoded proteins involved in sensing endogenous ligands (red bars). Of the 69 genes that are unchanged or upregulated, 45% encoded proteins involved in sensing infectious microbial ligands (blue bars and purple bars). Of the genes that are significantly upregulated ~62% (C3ar1_→_Ifitm6, p<0.008) encoded proteins involved in pathogen sensing and host defense. b-i. Comparative expression of genes involved in regulating the immune response in old vs. young microglia reveals a selective set of genes that are changed with normal aging. Values are mean ± SD of three different experiments done with microglia pooled from 22, 10 and 20 young mice, respectively and from three pools of microglia from 10 mice per pool., * indicates p<0.03.

Similar articles

Cited by

References

    1. Lawson LJ, Perry VH, Dri P, Gordon S. Heterogeneity in the distribution and morphology of microglia in the normal adult mouse brain. Neuroscience. 1990;39:151–70. - PubMed
    1. El Khoury J, et al. Ccr2 deficiency impairs microglial accumulation and accelerates progression of Alzheimer-like disease. Nat Med. 2007;13:432–8. - PubMed
    1. Rezaie P, Male D. Mesoglia & microglia--a historical review of the concept of mononuclear phagocytes within the central nervous system. J Hist Neurosci. 2002;11:325–74. - PubMed
    1. Nimmerjahn A, Kirchhoff F, Helmchen F. Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science. 2005;308:1314–8. - PubMed
    1. Block ML, Zecca L, Hong JS. Microglia-mediated neurotoxicity: uncovering the molecular mechanisms. Nat Rev Neurosci. 2007;8:57–69. - PubMed

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources