Nur77-deficiency in bone marrow-derived macrophages modulates inflammatory responses, extracellular matrix homeostasis, phagocytosis and tolerance
- Anouk A. J. Hamers1, 2,
- Carmen Argmann1, 3,
- Perry D. Moerland4,
- Duco S. Koenis1,
- Goran Marinković1,
- Milka Sokolović1, 5,
- Alex F. de Vos6,
- Carlie J. M. de Vries†1 and
- Claudia M. van Tiel†1Email author
© Hamers et al. 2016
Received: 24 April 2015
Accepted: 12 February 2016
Published: 1 March 2016
The nuclear orphan receptor Nur77 (NR4A1, TR3, or NGFI-B) has been shown to modulate the inflammatory response of macrophages. To further elucidate the role of Nur77 in macrophage physiology, we compared the transcriptome of bone marrow-derived macrophages (BMM) from wild-type (WT) and Nur77-knockout (KO) mice.
In line with previous observations, SDF-1α (CXCL12) was among the most upregulated genes in Nur77-deficient BMM and we demonstrated that Nur77 binds directly to the SDF-1α promoter, resulting in inhibition of SDF-1α expression. The cytokine receptor CX3CR1 was strongly downregulated in Nur77-KO BMM, implying involvement of Nur77 in macrophage tolerance. Ingenuity pathway analyses (IPA) to identify canonical pathways regulation and gene set enrichment analyses (GSEA) revealed a potential role for Nur77 in extracellular matrix homeostasis. Nur77-deficiency increased the collagen content of macrophage extracellular matrix through enhanced expression of several collagen subtypes and diminished matrix metalloproteinase (MMP)-9 activity. IPA upstream regulator analyses discerned the small GTPase Rac1 as a novel regulator of Nur77-mediated gene expression. We identified an inhibitory feedback loop with increased Rac1 activity in Nur77-KO BMM, which may explain the augmented phagocytic activity of these cells. Finally, we predict multiple chronic inflammatory diseases to be influenced by macrophage Nur77 expression. GSEA and IPA associated Nur77 to osteoarthritis, chronic obstructive pulmonary disease, rheumatoid arthritis, psoriasis, and allergic airway inflammatory diseases.
Altogether these data identify Nur77 as a modulator of macrophage function and an interesting target to treat chronic inflammatory disease.
KeywordsNur77 TR3 NR4A1 Macrophage Collagen Inflammation SDF-1α Rac1 CX3CR1
Nuclear receptor Nur77, also known as NR4A1, TR3 or NGFI-B, is a member of the NR4A receptor subfamily that also comprises Nurr1 (NR4A2, NOT) and NOR-1 (NR4A3, MINOR). Like other nuclear receptors, the NR4As consist of an N-terminal transactivation domain, a central zinc finger DNA binding domain (~94 % homology within the subfamily) and a C-terminal ligand binding domain. Structural analyses revealed that the NR4A receptors lack a classical hydrophobic ligand-binding pocket as a result of hydrophobic residues of amino-acid side chains, and so far no ligands have been identified [1, 2]. Nur77 is therefore referred to as an orphan nuclear receptor and its activity is regulated through gene expression, posttranslational modifications and coregulator interactions, as recently reviewed . Nur77 is a typical early response gene and its induction can be achieved with a plethora of stimuli among which peptide hormones, mitogens, physical stimulation and inflammatory factors. Known transcription factors inducing its expression include cyclic adenosine monophosphate (cAMP) responsive element binding protein (CREB), activator protein 1 (AP-1), NFκB, and myocyte enhancer factor 2 (MEF2). Nur77 can bind as a monomer to the so-called NGFI-B response element (NBRE; AAAGGCTA) in the promoter region of direct target genes. Nur77 and Nurr1 can also form homodimers and heterodimers with retinoid X receptor and bind a DR-5 response element . Furthermore, gene transcription is modulated by Nur77 itself through transrepression of other transcription factors. For example, Nur77 exhibits a direct, inhibitory interaction with the p65 subunit of NFκB [5, 6].
In macrophages, Nur77 is expressed in response to proinflammatory stimuli like prostaglandins, tumor necrosis factor-α (TNFα), lipopolysaccharide (LPS), interferon gamma (IFNγ) and granulocyte-macrophage colony stimulating factor (GM-CSF) [7, 8]. There may exist some discrepancy regarding Nur77’s anti-inflammatory role in macrophage function [7–13]. To elucidate the role of Nur77 in macrophages in more detail, we cultured bone marrow-derived macrophages (BMM) from wild-type (WT) and Nur77-deficient (Nur77-KO) mice, stimulated the cells with LPS and employed, to our knowledge for the first time, a gene expression study in these cells. Our data support functional involvement of Nur77 in (activated) macrophage physiology, by revealing the inhibition of stromal-derived factor (SDF)-1α expression, regulation of Rac1-mediated phagocytosis, extracellular matrix homeostasis and tolerance.
Expression profiling reveals that Nur77 modulates inflammatory gene expression in macrophages
In BMM Nur77 reduces SDF-1α promoter activity
Previously, we have shown that SDF-1α, also known as CXCL12, mRNA expression is increased in Nur77-KO BMM, independent of stimulation and that overexpression of Nur77 in Nur77-KO BMM normalized SDF-1α expression . In the current study, SDF-1α was also present in the top 25 of upregulated genes in Nur77-deficient BMM (Fig. 1 and Table S1).
Nur77 enhances expression of CX3CR1 in BMM
Modulation of extracellular matrix production in BMM by Nur77
Top 20 human disease pathway gene sets identified with GSEA that are upregulated in Nur77-KO vs WT BMM
Human disease pathways
Molecules contributing to the pathway
Diabetes mellitus type 1
NPY,CXCL12,DCN,HP,CALD1,IGF2,TAF5L, RAGE,VWF,CBLB,ENPP1,VEGFA,AGER,VDR, SOD3
Pulmonary disease, chronic obstructive
Carotid artery diseases
NPY,PDGFRA,VLDLR,HP,COL3A1,MMP2, CDKN2B,CDKN2A,F7,MMP3,MMP9,F2R, HMGCR,VWF,ENPP1,VEGFA,APOE,VDR,LDLR,ESR1,SCARB1
Carcinoma ductal breast
In line with our previous observations, CXCL12/SDF-1α expression was higher in Nur77-KO BMM than in WT cells. Even though Nur77 transrepresses NFκB p65, Nur77 did not affect NFκB p52 activity. Rather, direct binding of Nur77 to the SDF-1α promoter was shown to be crucial to inhibit expression of this gene. It was unexpected to detect diminished MMP9 activity, increased TIMP1-3 gene expression and enhanced expression of several collagen subtypes, among which Col1a1, present in the list of top-25 regulated genes, Col6a1 and Col12a1. Of note, Wang et al.  recently demonstrated that Nur77 augments MMP9 expression in colorectal cancer cells promoting invasion and metastasis of colorectal cancer. Corresponding with these observations, Nur77-KO BMM were shown to synthesize more collagen in their subcellular matrix compared to WT macrophages. This aspect of macrophages is relevant to wound healing, however, wound closure is normal in Nur77-KO mice . Wound healing is a complex process involving multiple cell types, which may explain why overexpression of a dominant-negative variant of Nur77 in endothelial cells disturbs normal wound healing. In a similar way, Nur77 may need to be studied in more detail in macrophages during wound healing.
The most strongly downregulated gene in the absence of Nur77 was CX3CR1, which is especially expressed on colon lamina propria macrophages that sample antigen from the intestinal lumen . CX3CR1high macrophages produce IL-10, contributing to the maintenance and local expansion of protective regulatory T cells in the gut . CX3CR1 expression was not only decreased in Nur77-KO BMM, but also in colon samples of these mice compared to WT colon. Previously, we have shown that IL-10 production by Nur77-KO BMM is lower compared to WT BMM . Together, these data indicate a role for Nur77 in macrophage tolerance towards host bacteria in the gut and recently we have shown that dysregulation of Nur77 expression indeed leads to enhanced development of inflammatory bowel disease . In the IPA upstream regulator analysis, we found the small GTPase Rac1 as an intriguing, unknown regulator of Nur77-mediated gene expression, which by itself is regulated by Nur77-deficiency. Rac1 is critically involved in cytoskeletal rearrangements [40, 41] and thus important in cell motility. In macrophages, it predominantly regulates Fcγ receptor-mediated phagocytosis [33, 34], cell fusion  and migration . We found increased Rac1 activity upon Nur77 deficiency in BMM and a drastic increase in phagocytic capacity of Nur77-KO BMM in an E.coli opsonization model. These data strongly support our previous finding that Nur77-KO mice show a better initial clearance of bacteria during E.coli-induced peritonitis . The latter study showed that the responsiveness of peritoneal macrophages to E. coli was only mildly affected by Nur77-deficiency, which is in line with our microarray data that reveal a limited effect of Nur77-deficiency on LPS-induced changes in gene expression (Additional file 1: Tables S5 and S6).
Our unbiased analyses of signaling pathways and diseases resulted in multiple hits relating to vascular disease and atherosclerosis. More specifically, gene sets identified with GSEA are; ‘Signaling by PDGF, Smooth muscle cell contractions, Sphingolipid metabolism and CXCR4 pathway’ [44–46] (Additional file 1: Table S3). In addition, GSEA revealed ‘carotid artery diseases’ and ‘coronary disease’ in the top 20 of human disease pathways, whereas ‘atherosclerosis signaling’ was found in IPA amongst the top 25 of canonical pathways associated with differentially expressed genes in Nur77-KO versus WT BMM (Fig. 4 and Additional file 1: Table S2). Altogether, the analyses on BMM gene expression support the protective function of Nur77 in atherosclerosis [10, 12, 24]. The other two members of the same subfamily of nuclear hormone receptors, Nurr1 and NOR-1, are also expressed in human atherosclerotic lesion macrophages and were shown to repress LPS-induced inflammatory response in THP-1 macrophages . Similarly as Nur77, transplantation of bone marrow deficient for NOR-1 into atherosclerotic mice, aggravates the formation of atherosclerotic lesions .
Even though our gene expression analyses were performed in macrophages, a potential involvement of Nur77 in ‘diabetic nephropathy, angiopathy and retinopathy and glucose intolerance’ was predicted from GSEA (Table 1), which may emphasize the relative importance of macrophages in these pathologies. Macrophages are indeed known to contribute to the nephropathies [48–52], angiopathies [53, 54] and retinopathy [55, 56] seen in diabetes. Nur77 regulates hepatic glucose homeostasis  and Nur77-deficiency causes increased diet-induced insulin resistance . Regarding the recent observation that lipid storage by adipose tissue macrophages regulates systemic glucose tolerance , it may be interesting to investigate glucose tolerance after a Nur77-deficient bone marrow transplantation into Ob/Ob mice.
Finally, we found multiple, often chronic inflammatory diseases to be potentially influenced by macrophage Nur77 expression. In most of these diseases macrophages are known to play a role. GSEA (Table 1) revealed osteoarthritis, chronic obstructive pulmonary disease and macular degeneration, whereas IPA (Additional file 1: Table S2) associated Nur77 to rheumatoid arthritis, psoriasis and allergic airway inflammatory diseases. Interestingly, recently Kurakula et al.  showed a protective role for Nur77 in ovalbumin-induced airway inflammation. Nur77 expression is elevated in synovial tissue, cartilage and prostaglandin E2 (PGE2) stimulated chondrocytes from patients with rheumatoid arthritis, psoriatic arthritis or osteoarthritis, making Nur77 an attractive target in rheumatic diseases [60–63]. In addition, T cell-specific Nur77 overexpression results in reduction of incidence and severity of collagen-induced arthritis by promoting activation-induced T cell apoptosis and inhibition of CollagenII-specific antibody production . Interestingly, Nurr1 has already been shown to modulate psoriasis and rheumatoid arthritis [60, 61, 65]. The observed associations reveal potential, and so far speculative, connections between Nur77 and rheumatoid arthritis, macular degeneration, psoriasis and chronic obstructive pulmonary disease and we therefore propose that it may be relevant to study the role of Nur77 in these diseases.
Our transcriptome analysis to explore the role of Nur77 in macrophage function uncovered involvement of Nur77 in extracellular matrix modulation, macrophage tolerance and inhibition of phagocytosis and insight in its potential function in several diseases. In summary, as schematically shown in Fig. 6, Nur77 modulates the inflammatory state of macrophages by decreasing inflammatory gene expression in macrophages via NFκB transrepression and positively regulating CX3CR1 expression. Nur77 directly represses SDF-1α secretion, which may result in less chemo-attraction of inflammatory cells. In addition, Nur77 inhibits the collagen content of the extracellular matrix of macrophages, diminishes Rac1 activity and reduces phagocytosis of these cells. All these effects can influence a plethora of inflammatory and metabolic diseases, making Nur77 an interesting factor to study and maybe even to target in treatment of chronic inflammatory disease.
Nur77-KO mice  on a C57BL/6 background were kindly provided by Prof B.R. Binder (Vienna, Austria). All animal experiments were approved by the Committee for Animal Welfare of the Amsterdam Medical Center and were carried out in compliance with guidelines issued by the Dutch government.
Macrophage cell culture and transfection
Each batch of bone marrow cells was isolated from femurs and tibiae of three wild-type (WT) mice and three Nur77-KO mice as described . In brief, cells were cultured in RPMI-1640 (GIBCO Invitrogen) with 100 U/ml penicillin/streptomycin (GIBCO Invitrogen), 10 % heat-inactivated fetal calf serum (FCS; GIBCO Invitrogen) and 15 % L929 conditioned medium (LCM) for 8 days to generate BMM. BMM were seeded at a density of 1.5 × 105 cells/cm2 24 h before stimulation. In WT BMM Nur77 was knocked-down by lentiviral transduction with a short hairpin (sh-)Nur77 cloned into a p156RRL-sinPPT-CMV-GFP-PRE/NheI vector by Bonta et al.  Lentiviral particles were produced as described previously  and BMM were transduced for 24 h with recombinant lentivirus. After transduction, cells were cultured for another 24 h and thereafter stimulated with 100 ng/ml LPS. shCON lentivirus was taken along as a control. Knockdown was confirmed by qPCR.
RAW264.7 cells were cultured in RPMI-1640 supplemented with 10 % FCS and penicillin/streptomycin and were transfected using Lipofectamine LTX (all Invitrogen) according to the manufacturer’s instructions.
RNA was isolated from Nur77-KO and WT BMM using the Aurum total RNA isolation kit (BioRad) and samples were sent to ServiceXS (Leiden, The Netherlands) for further microarray processing. In brief, to assess the quality of the samples, the concentration of the RNA was determined using the Nanodrop ND1000 spectrophotometer. The Agilent Bioanalyzer was used to analyze the quality and integrity of the RNA samples. The Illumina TotalPrep-96 RNA Amplification Kit was used to generate biotin labeled (biotin-16-UTP) amplified cRNA and the obtained biotinylated cRNA samples were hybridized onto the Illumina MouseWG-6 v2 arrays. The samples were scanned using the Illumina iScan array scanner and the data retrieved using Illumina’s Genomestudio v. 2011.1 software.
Microarray pre-processing and data analysis
Analyses were carried out with Bioconductor packages in the statistical software package R (version 2.14.0). Normexp-by-control background correction, quantile normalization, and log2 transformation  were performed on the Illumina sample and control probe profiles using the limma package (version 3.10.2). The arrayQualityMetrics package (version 3.10.0) was used to assess whether the microarray data were of good quality. Only probes detected (detection p-value < 0.05) on at least one array were included in the differential expression analysis. Gene-wise linear models were fitted using the limma package. Differential expression between the different conditions was assessed via a moderated t-test. The illuminaMousev2.db package (version 1.12.2) was used to update the probe annotation provided by Illumina. The data set with differentially expressed genes (nominal p-value < 0.05) was analyzed using Ingenuity Pathway Analysis (IPA, Ingenuity Systems) to test for enriched canonical pathways, to identify biological functions that are expected to be affected and to identify upstream transcriptional regulators. The background set for the gene enrichment analyses consisted of all genes that were detected on at least one array. Significance of enrichment was calculated using a right-tailed Fisher’s Exact Test.
Gene set enrichment analysis (GSEA; version 2.2.0 ,) was performed using default options except for the following: the permutation type = Geneset; and the number of permutations = 1000 [69, 70]. The gene set collection c2.cp.v5.0.symbols.gmt which includes canonical pathways was queried in this analysis. The gene set to query human diseases was derived from  and GSEA was performed as described above except that the minimum number of genes in a gene set was set at 4.
A construct containing amino-terminally myc-tagged Nur77 has been described before . Two fragments of the murine SDF-1α promoter containing a putative NBRE (from −500 to +18 bp and from −1023 to +18 bp relative to the transcriptional start site) were cloned into the pGL3 basic vector (Promega) in front of the firefly luciferase gene. The mutant of the promoter constructs in which the putative NBRE was disrupted was generated by site-directed mutagenesis using the QuickChange site-directed mutagenesis method (Stratagene) according to the manufacturer's instruction using the following primer: dNBRE forw: 5’-ctgggaagatcaaagAActcagcacccagcgg-3’ and dNBRE rev: 5’-ccgctgggtgctgagTTctttgatcttcccag-3’. The nucleotides in capital letters represent the mutated nucleotides in the SDF-1α promoter. The construct was verified by sequencing and did not contain any other sequence variations.
NFκB p52 activation/binding
BMM were stimulated with either 100 ng/ml LPS for 1 h or 25 μg/ml CD40 activating antibody FGK45 (Bioceros BV) for 3 h, protein lysates were harvested and the levels of active p52 were determined using the TransAM NFκB family kit (Active Motif) according to the manufacturer’s protocol. The absorbance was measured at OD450 nm in a microplate reader (EL808, Bio-Tek instruments).
Luciferase reporter assays
RAW264.7 cells were transiently transfected with wild-type or mutant SDF-1α luciferase reporter plasmids together with pCMV-Myc-Nur77 or pCMV-mock. pRL-TK Renilla reporter plasmid (Promega) was co-transfected as an internal control. Luciferase activity measurements were performed using the dual-luciferase reporter assay system (Promega) and Glomax Multi detection system (Promega) according to the manufacturer’s instructions. Each experiment (in duplicate) was repeated at least three times.
Chromatin immunoprecipitation assay (ChIP)
BMM were infected with Mock- or Nur77-adenovirus at a MOI of 100 for 4 h, and 28 h after infection the cells were harvested for ChIP analysis. ChIP assays were performed using the Magnify ChIP system (Invitrogen) according to the manufacturer’s instructions. The following primers were used to amplify the SDF-1α promoter in semi-quantitative real-time (qRT)PCR: 5’-GACTGTTTCGTCTCTCAGGTTC-3’ (sense) and 5’-GCTGAGACCTTTGATCTTCCCA-3’ (antisense).
Total RNA was extracted using the Aurum™ Total RNA Mini Kit (Biorad) and cDNA was made from 500 ng RNA using iScript cDNA Synthesis kit (BioRad). qRT-PCR was performed using iQ SYBR Green Supermix (BioRad) and was measured using the MyIQ system and the following primers: Cx3cr1 forw: 5’-gagtatgacgattctgctgagg-3’ and Cx3cr1 rev: 5’-cagaccgaacgtgaagacgag-3’. Ribosomal protein 36B4 expression was determined to correct for cDNA content (36B4 forw: 5’-ggacccgagaagacctcctt-3’, 36B4 rev: 5’-gcacatcactcagaatttcaatgg-3’).
Western blot analysis
BMM were treated for 24 h with 100 ng/ml LPS, after which the cells were washed twice with PBS and lysed in ice-cold Nonidet P-40 (NP-40) lysis buffer (50 mM Tris–HCl pH7.4, 100 mM NaCl, 10 mM NaF, 1 mM Na3PO4, 10 % glycerol, 1 % NP-40). After a 10 min incubation on ice the lysates were collected and boiled in sample buffer containing DTT. Samples were thereafter analyzed by SDS-PAGE. All proteins of interest were separated on 12 % polyacrylamide SDS gels. Proteins were transferred to 0.2 μm nitrocellulose membranes using the Trans-blot Turbo transfer system (Biorad). Nitrocellulose membranes were subsequently blocked in 5 % (w/v) non-fat milk in Tris-buffered saline (TBS) and incubated with CX3CR1 (Santa Cruz) and anti-α-tubulin (Cedarlane) primary antibodies overnight at 4 °C, followed by horse radish peroxidase-labelled secondary antibodies (Bio-Rad) for 1 h. Proteins were visualized with an enhanced chemiluminescence (ECL) detection system (Thermoscientific) and quantification of signal was performed using intensity measurements in ImageJ software.
Collagen content assay
Collagen content of WT and Nur77-KO BMM was measured as described before . Briefly, BMM were seeded at a density of 2 × 105 cells/well in 24-wells plates. Cells were rinsed with PBS and fixed with 4 % para-formaldehyde and collagen content was stained by incubating with a 0.1 % (w/v) solution of Sirius Red F3B dye (BDH Laboratory Supplies) in 10 mM HCl for 40 min. Unbound dye was removed by washing extensively with 10 mM HCl, after which 100 mM NaOH was added to dissolve the dye and the absorbance was measured at OD550 nm in a microplate reader (EL808, Bio-Tek instruments).
Gelatinolytic metalloproteinase activity, especially MMP2 and MMP9, in WT and Nur77-KO BMM was measured by separating lysates of these cells on 10 % polyacrylamide gels containing gelatin (Ready-Gel zymogram gels, BioRad) under non-reducing conditions. After electrophoresis, the proteins were renatured by placing the gels in 2.5 % Triton X-100 for 30 min at room temperature and developed overnight in developing solution (50 mM Tris–HCl, pH 7.5, 200 mM NaCl, 5 mM CaCl2, 0.02 % Brij-35), followed by staining with PageBlue Protein Staining Solution (Thermo Scientific). After destaining with MilliQ, gelatinase activity was measured by densitometry.
Rac1 activity assay
WT and Nur77-KO BMM were treated for 16 h with Rac1 inhibitor (553502; Calbiochem) followed by a 24-h incubation with 50 ng/ml interferon-γ (IFNγ, Peprotech). Cell lysates were prepared and the levels of Rac1-GTP were measured using a colorimetric-based G-LISA Rac1 (BK128; Cytoskeleton) activation assay according to the manufacturer’s protocol. OD490 nm was measured with a microplate reader (EL808, Bio-Tek instruments). Absorbance units in each sample were expressed after subtraction of the background units measured in protein-free lysis buffer.
BMM were cultured overnight at 37 °C in RPMI containing 10 % FCS at a density of 0.5x106 cells/well in 12-wells plates. BMM were washed twice with Hanks' balanced salt solution (GIBCO/Invitrogen) prior to the addition of fluorescently labeled bacteria. Uropathogenic E. coli (strain 1677)  were heat-killed by incubation at 65 °C for 1 h and labeled with 0.2 mg of FITC (Sigma-Aldrich) per ml in 0.1 M NaHCO3 (pH 9.0) for 1 h at 37 °C. The FITC-labeled E. coli (equivalent to 50 × 106 CFU) were added to the BMM at a ratio of 100:1 and incubated for 1 h at 37 °C or 4 °C. Phagocytosis was stopped by immediately transferring the cells to 4 °C and washing them with ice-cold PBS containing 2 mM EDTA. The cells were harvested by gentle scraping and were subsequently treated with 0.4 % Trypan blue (GIBCO/Invitrogen) to quench extracellular fluorescence, washed twice with PBS/EDTA, and analyzed using a flow cytometer (Becton Dickinson FACScalibur). Results were expressed as phagocytosis index, defined as the percentage of cells with internalized E. coli times the mean fluorescence intensity.
Data are reported as mean ± S.D. and were analyzed with the unpaired Student’s t test. Values of p < 0.05 were considered statistically significant (*p < 0.05, **p < 0.01, ***p < 0.001 in the figures).
Availability of supporting data
The microarray data have been deposited in NCBI Gene Expression Omnibus in a MIAME compliant format and are accessible under GEO Series accession number GSE68167.
This study was supported by the Netherlands Heart Foundation, The Hague; grant #2008B037 and by the research program of the BioMedical Materials institute, co-funded by the Dutch Ministry of Economic Affairs as a part of Project P1.02 NEXTREAM. We acknowledge the support from the Netherlands CardioVascular Research Initiative: the Dutch Heart Foundation, the Netherlands Federation of University Medical Centres, the Netherlands Organisation for Health Research and Development and the Royal Netherlands Academy of Sciences for the GENIUS project (CVON2011-19).
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