The islet-resident macrophage is in an inflammatory state and senses microbial products in blood

Abstract

We examined the transcriptional profiles of macrophages that reside in the islets of Langerhans of 3-wk-old non-obese diabetic (NOD), NOD.Rag1^-/-, and B6.g7 mice. Islet macrophages expressed an activation signature with high expression of Tnf, Il1b, and MHC-II at both the transcript and protein levels. These features are common with barrier macrophages of the lung and gastrointestinal tract. Moreover, injection of lipopolysaccharide induced rapid inflammatory gene expression, indicating that blood stimulants are accessible to the macrophages and that these macrophages can sense them. In NOD mice, the autoimmune process imparted an increased inflammatory signature, including elevated expression of chemokines and chemokine receptors and an oxidative response. The elevated inflammatory signature indicates that the autoimmune program was active at the time of weaning. Thus, the macrophages of the islets of Langerhans are poised to mount an immune response even at steady state, while the presence of the adaptive immune system elevates their activation state.

Figure 1.

Transcriptional profiling of islet-resident macrophages. Top expressed housekeeping (A) and myeloid (B) genes from NOD, NOD.Rag1^−/−, and B6.g7 islet macrophages and DCs. Macrophages and DCs were isolated as indicated in Fig. S1. (C) Core macrophage-specific gene signature (as defined by Gautier et al., 2012), distinguishing macrophages from DCs. Expression of costimulatory genes (D), genes encoding TLRs and adaptors (E), chemokines (F), and chemokine receptors (G) by islet macrophages and PLN DCs. Costimulatory gene selection was based on Chen and Flies (2013). TLR and TLR adaptors were based on Chevrier et al. (2011). Chemokines and chemokine receptors were based on Griffith et al. (2014). Data are the mean of three or four samples per group and are represented as the log₂ global expression level.

Figure 2.

Analysis of islet macrophage transcriptional diversity. (A) PCA of the 5% of genes with the greatest variability for XCR1⁺ DCs, NOD CD11b⁺ lung macrophages, and NOD, NOD.Rag1^−/−, and B6.g7 islet macrophages. (B) Pearson’s correlation matrix of macrophages and DCs on the basis of all expressed RNASeq probes. (C) Hierarchical clustering of macrophages and DCs for the top 5% of genes with the greatest variability. (D) Scatterplots of expression values of all annotated genes. (E) Heat map of differentially expressed genes taken from D. Each dot represents the mean of four independent biological replicates for NOD and three for NOD.Rag1^−/− conditions. Numbers in plots indicate probes with a DESeq2-calculated fold change between conditions of ≥2 and adjusted P ≤ 0.05 at an FDR of 5% (red, up-regulated in NOD; blue, up-regulated in NOD.Rag1^−/−). (F) GO and canonical (C2) pathway hypergeometric analysis of the genes differentially expressed between NOD and NOD.Rag1^−/− islet macrophages. (G) Enrichment plots from GSEA analysis performed on differentially expressed genes using GO biological process (MSigDB C5BP) signature gene sets. ES, enrichment score. Heat maps of core enrichment genes from “inflammatory response” (H), “behavior” (I), “response to oxidative stress” (J), and “oxidative phosphorylation” (K) gene sets, identified by either GO (F) or GSEA (G). Heat maps show individual samples and represent the log₂ row normalized expression.

Figure 3.

Early inflammatory signature during diabetogenesis. (A) Pearson’s correlation of samples from Carrero et al. (2013) on the basis of genes identified using DESeq2 as differentially up-regulated in NOD versus NOD.Rag1^−/− macrophages with adjusted P ≤ 0.05 and fold change ≥2. (B) Hierarchically clustered genes from A in whole-islet transcriptome analysis (top). The Z-score profiles of genes expression in cluster I (red) and cluster II (green) are shown (bottom). Sample number ranged from three to six per group. Each column represents data obtained from one biological replicate each composed of all the intact islets isolated from one mouse of the indicated genotype. (C and D) Hypergeometric analysis of the genes identified in clusters I and II in B using GO biological pathways and C2 canonical pathways.

Figure 4.

Islet macrophages are similar to barrier macrophages. (A) GSEA enrichment plots of NOD versus NOD.Rag1^−/− islet macrophage differences on the basis of LPS, TNF, and IL-1 signatures. The differences between NOD and NOD.Rag1^−/− were compared with published signatures of LPS, TNF, and IL-1 cells as described in Materials and methods. ES, enrichment score. (B) Hierarchical clustering of ImmGen microarray data for macrophages from different tissues. The LPS signature genes were selected for clustering the macrophage microarray data from ImmGen. Heat map shows the log₂ row normalized expression. (C) LPS, TNF, and IL-1 signatures from bone marrow and lung (CD103^negCD11b⁺) macrophage microarrays (ImmGen), and lung and islet macrophages from the present study. All expressed genes were ranked by expression level, and genes that match to the signatures are depicted as horizontal lines. (D) Schematic illustration of expression levels of the LPS, TNF, and IL-1 signatures genes in different macrophages. (E) GSEA enrichment plot of the lysosome gene pathway, the top canonical (C2, MSigDB) pathway up-regulated in islet macrophages when compared with CD11b⁺ lung macrophages. (F) Heat map of the core enrichment genes from E. Heat map shows individual samples and represent the log₂ row normalized expression.

Figure 5.

Flow cytometric evaluation of islet macrophages for transcriptionally identified markers. (A) The islets and lungs of 3-wk-old NOD and NOD.Rag1^−/− mice were isolated and single-cell suspensions were made. Cells were stained with antibodies against cell surface markers and then fixed and stained with antibodies against intracellular pro-form IL-1β and TNF. Plots were gated on CD45⁺CD11c⁺MHC-II⁺CD11b⁺F4/80⁺. The percentages of cells positive are indicated in each quadrant. Results are representative of three independent experiments per condition. (B) Graphs of the percentage of macrophages positive for either TNF or IL-1β as determined in A. Bars show the mean ± SD for at least three independent experiments per condition.

Figure 6.

Inflammatory status of islets before and after treatment with LPS. (A) NOD or NOD.Rag1^−/− mouse islet macrophages were isolated and stained with the intracellular caspase-1 substrate FAM FLICA YVAD-FMK. The black histograms are gated on the CD45-negative fraction of the islets, and the gray histograms are gated on macrophages as in Fig. S1. Mean fluorescent intensity (MFI) is indicated on the graphs. MFIs for active caspase-1 ranged from 62.5–102 (mean 72.2) for the CD45^neg population and from 388–884 (mean 625) for the F4/80⁺ population. Data are representative of two or three independent experiments per group. (B) Islets from 6-wk-old NOD mice were isolated, dispersed, and cultured overnight in chamber slides in the absence or presence of IL-1β. Cells were then stained with DAPI (blue) and anti-RelA/p65 (red). Cells were imaged by confocal microscopy. Bar, 4 µm. Image is representative of three independent experiments. (C) Expression of inflammatory gene transcripts in macrophages isolated from islets of mice intravenously injected with LPS. The indicated mice were treated with either PBS (UT) or LPS IV (LPS). Then, islet macrophages were flow-sorted, RNA was isolated, and qRT-PCR was performed on the indicated markers. Each symbol represents one individually sorted sample. Horizontal bars show the mean. Significance was tested using the Mann-Whitney U test. *, P < 0.0332; **, P < 0.0021; ***, P < 0.0002. Graphs show all the data from at least three independent experiments performed in duplicate for each condition.

Figure 7.

Single-cell qRT-PCR of islet macrophages reveals NOD heterogeneity. (A) PCA of the single-cell qRT-PCR results. The samples circled in black were all Cxcl9⁺, whereas no Cxcl9⁺ cells were found in the rest of the samples. PC, principal component. (B) Volcano plot of the fold change (FC; log₂) expression between NOD and NOD.Rag1^−/− compared with the ANOVA p-value (log₁₀). Genes in the upper right quadrant had greater than twofold higher expression on average in NOD versus NOD.Rag1^−/− and were significantly differentially expressed by ANOVA at P < 0.01.