Article Figures & Data
Figures
- FIGURE 1.
Identification of genes induced in whole blood directly by TLR7/8 activation or secondarily by IFN.
Human whole blood was pretreated in the absence or presence of anifrolumab (1 μg/ml) for 15 min, followed by treatment for 1 or 24 h with R848 (1 μM), IFN-α (100 U/ml), or DMSO at 37°C. After incubation, the blood was added to PAXgene RNA Tubes for preservation, and RNA was subsequently extracted and analyzed for gene expression by NanoString. The heat map shows the log2 fold change compared with the DMSO group at each timepoint. Only genes with a log2 fold change >1 are presented. Data are the average of two donors and representative of two separate experiments.
- FIGURE 2.
Gene expression analysis to characterize sorted cell types.
Cells were sorted from human blood by FACS into individual populations, and RNA was isolated and analyzed by NanoString using the Human Immunology Panel 2.0 (A). The fold change for each gene in each cell type versus the mean expression for all cell types was calculated, and the results are plotted as a heat map (A). Several genes found to be representative of each cell type are listed above the heat map. The expression of TLR7/8 and IFN pathway receptors in each cell type is shown (B) as a heat map with coloring based on the normalized counts for each gene in each cell type. The data are representative of two separate experiments testing two different donors.
- FIGURE 3.
Treatment of whole blood with TLR-selective agonists and cell sorting identifies cell type–specific genes induced by TLR7/8 activation.
Human whole blood was treated with the TLR7-selective agonist CL-087 or the TLR8-selective agonist motolimod for 1 or 24 h, and then FACS was used to isolate individual cell types. RNA was purified from the sorted cells and analyzed for gene expression by NanoString. The heat maps show gene expression after 1 (A) or 24 h (B) of treatment, and coloring shows the log2 fold change compared with the 1 h DMSO control for each cell type. The data presented are the average of two experiments using two separate donors. Gran, granulocyte; Mono, monocyte.
- FIGURE 4.
Analysis of IFN subtypes by quantitative PCR (QPCR).
To confirm the results of the NanoString analysis for IFN isoforms, the same RNA samples from Fig. 3 were analyzed by QPCR for expression of IFNA1, IFNA2, and IFNB1. GAPDH was measured as a housekeeping gene for normalization, and the fold change compared with the 1-h DMSO sample for each cell type was calculated. The data presented are the average of two experiments using two separate donors. Gran, granulocyte; Mono, monocyte.
- FIGURE 5.
Correlation of TLR7 and TLR8 stimulation effects on gene expression in myeloid cells.
The log2 fold change induced by TLR7 or TLR8 activation is plotted for the three most highly activated cell types from Fig. 3. Genes induced specifically by TLR7 are colored green, by TLR8 specifically are colored blue, and by both TLRs are colored red. The data presented are the average of two experiments using two separate donors.
- FIGURE 6.
Flow cytometry analysis of intracellular cytokine expression after TLR7 and TLR8 activation.
Human PBMCs were treated with brefeldin A and then stimulated with the TLR7-selective agonist CL-087 or the TLR8-selective agonist motolimod for 4 h and then analyzed for intracellular cytokine expression by flow cytometry. The expression of cytokines in different cell populations is shown as histograms (A) for one representative donor for five different cell populations. The percentage of each cell population staining positive for each cytokine was determined, and the results for four donors from two separate experiments are presented (B). Each individual donor is represented by a dot, and the group means and SD are represented as bars. Mo, monocyte.
- FIGURE 7.
viSNE analysis of flow cytometry intracellular cytokine staining.
To study the expression of cytokines in individual cells in different populations, viSNE analysis was performed on the data from Fig. 6, and representative results from one of the four donors tested are presented. The different cell populations are gated and labeled, and the intensity of staining for each subset identifying marker and cytokine is shown by coloring.
- FIGURE 8.
Anti-IFNAR treatment reduces a subset of disease genes in lupus mice and defines specifically IFN-regulated genes.
Lupus-like disease was induced in DBA/1 mice by injection of pristane i.p. At 8 wk after pristane injection, mice were treated with an anti–IFNAR-1 Ab (α-IFNAR) or PBS (Vehicle) three times per week. After 1, 2, or 4 wk of treatment, blood samples were collected, and RNA was isolated for gene expression analysis by NanoString. The log2 fold change in expression was calculated for each mouse compared with a nonpristane-injected healthy control (HC) group. The heat map (A) shows the log2 fold change for the group mean of each condition (n = 4). The genes increased >1 log2 fold change by disease at week 4 are shown in a plot for the mean of the vehicle group versus the mean of the α-IFNAR group (B). Genes significantly affected by α-IFNAR treatment are shown in purple. An IFN score and an NF-κB score were calculated for each mouse using canonical genes for each pathway, and the group means are plotted (C). The data shown are from one experiment with four mice per group and are representative of two separate experiments.
- FIGURE 9.
Correlation of gene expression and autoantibodies in SLE patients.
Blood samples were collected into PAXgene RNA Tubes from healthy volunteers (n = 11) and SLE patients (n = 39), and RNA was extracted and analyzed for gene expression by NanoString. The heat map (A) shows the log2 fold change mean for each gene for the SLE patient group compared with the healthy volunteer group. Plasma samples were also collected from the patients and analyzed using a 128-Ag microarray to test for autoantibodies common to autoimmune diseases (B). The z-scores were calculated for the SLE patients relative to the healthy volunteer group, and a Spearman correlation analysis was run. The autoantibody with the highest correlation in expression for each gene is shown with the R values and p values displayed in the blue and green heat maps, respectively.
- FIGURE 10.
Model of the cell types affected by TLR7/8 activation over time.
Based on the results of the studies reported in this paper, a hypothetical model of TLR7 and TLR8 activation in the blood is proposed. TLR7 activation initially stimulates IFN-β and inflammatory cytokines regulated by NF-κB and later production of IFN-α, which then have secondary effects on multiple cell types. TLR7 activation can also stimulate B cells, but the consequence is not primarily cytokine production. TLR8 activation at early timepoints stimulates granulocytes, monocytes, and DCs to produce IFN-β and a multitude of inflammatory cytokines, and the response is greater in magnitude than that stimulated by TLR7. IFN-β production decreases over time, whereas the initial wave of inflammatory cytokine production has a broad secondary effect on multiple cells resulting in greater and more sustained inflammatory activity.
Tables
Autoantibody IFN Hi Autoantibody+ (n) IFN Lo Autoantibody+ (n) IFN Hi Autoantibody+ (%) IFN Lo Autoantibody+ (%) p Value Nucleosome Ag 24 4 85.7 36.4 1.41 × 10−3 ssRNA 19 2 67.9 18.2 4.20 × 10−3 Chromatin 21 3 75.0 27.3 4.90 × 10−3 Collagen VI 17 2 60.7 18.2 1.61 × 10−2 Heparin 16 2 57.1 18.2 2.81 × 10−2 Genomic DNA 17 3 60.7 27.3 6.25 × 10−2 U1-snRNP-C 13 2 46.4 18.2 1.08 × 10−1 Ro-52/SSA 10 7 35.7 63.6 1.20 × 10−1 dsDNA 24 7 85.7 63.6 1.31 × 10−1 Ribo phosphoprotein P0 12 2 42.9 18.2 1.56 × 10−1 ssDNA 13 4 46.4 36.4 5.80 × 10−1 PM/Scl-100 14 5 50.0 45.5 8.05 × 10−1 Autoantibody+ defined as z-score >3.
Data Supplement
