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The Journal of Immunology, 2005, 174: 834-845.
Copyright © 2005 by The American Association of Immunologists

Transcriptional Profiling Reveals Complex Regulation of the Monocyte IL-1{beta} System by IL-131

Chris J. Scotton2,*, Fernando O. Martinez*,{dagger}, Maaike J. Smelt*, Marina Sironi*, Massimo Locati{dagger}, Alberto Mantovani*,{dagger} and Silvano Sozzani3,*,{ddagger}

* Istituto di Ricerche Farmacologiche Mario Negri, and {dagger} Section of General Pathology, University of Milan, Milan, Italy; and {ddagger} Section of General Pathology and Immunology, University of Brescia, Brescia, Italy


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
IL-4 and IL-13 are prototypic Th2 cytokines that generate an "alternatively activated" phenotype in macrophages. We used high-density oligonucleotide microarrays to investigate the transcriptional profile induced in human monocytes by IL-13. After 8-h stimulation with IL-13, 142 genes were regulated (85 increased and 57 decreased). The majority of these genes were related to the inflammatory response and innate immunity; a group of genes related to lipid metabolism was also identified, with clear implications for atherosclerosis. In addition to characteristic markers of alternatively activated macrophages, a number of novel IL-13-regulated genes were seen. These included various pattern recognition receptors, such as CD1b/c/e, TLR1, and C-type lectin superfamily member 6. Several components of the IL-1 system were regulated. IL-1RI, IL-1RII, and IL-1Ra were all up-regulated, whereas the IL-1{beta}-converting enzyme, caspase 1, and IRAK-M were down-regulated. LPS-inducible caspase 1 enzyme activity was also reduced in IL-13-stimulated monocytes, with a consequent decrease in pro-IL-1{beta} processing. These data reveal that IL-13 has a potent effect on the transcriptional profile in monocytes. The IL-13-induced modulation of genes related to IL-1 clearly highlights the tightly controlled and complex levels of regulation of the production and response to this potent proinflammatory cytokine.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Monocytes and macrophages (M{phi})4 play a central role in both innate and adaptive immunity. They constitute a nonspecific first line of defense by phagocytosing opsonized or nonopsonized microorganisms; they can also act as APCs, thereby stimulating a specific immune response. Monocytes are derived from CD34+ myeloid progenitor cells in the bone marrow, and subsequently leave the bone marrow to circulate in the bloodstream (1). Inflammation due to tissue damage or infection results in the production of cytokines, chemokines, and other inflammatory mediators, which can influence monocyte function, causing recruitment to the site of inflammation and differentiation into M{phi}. Different subpopulations of activated M{phi} exist, depending on the type of stimulus they receive. M{phi} are currently divided into "classically activated," "type 2-activated," and "alternatively activated" populations (see Refs.2, 3, 4 for recent review).

In classical activation, exposure of M{phi} to IFN-{gamma} primes the cells to respond to further stimulation by TNF-{alpha} or an inducer of TNF-{alpha}, frequently LPS or other bacterially derived products. These cells secrete various cytokines and chemokines including TNF-{alpha}, IL-12, IL-6, and CCL2; they up-regulate expression of MHC class II and CD86, and they produce NO and O2– (3, 5, 6, 7). These cells are particularly important for killing and degrading intracellular pathogens.

Type 2-activated M{phi} arise from Fc{gamma}R ligation followed by stimulation of TLR, CD40 or CD44. These cells produce many of the cytokines seen in classically activated M{phi} (e.g., TNF-{alpha} and IL-6), but they switch off IL-12 production and secrete large quantities of IL-10 (8, 9, 10). These cells therefore exert a potent anti-inflammatory effect, and because IL-10 can stimulate IL-4 production by T cells, they also preferentially induce a Th2 response (11).

In contrast, alternatively activated M{phi} are induced by IL-4, IL-13, or glucocorticoids. They secrete IL-10 and IL-1Ra and have increased expression of scavenger receptor and mannose receptor, but they are poor producers of reactive oxygen species or NO (3). Thus, these cells are unable to efficiently kill intracellular pathogens. The up-regulation of mannose receptor (12) may increase the potential for alternatively activated M{phi} to present Ag, as has been shown for dendritic cells (DC) (13, 14), but these M{phi} can also inhibit the proliferation of T cells under certain circumstances (15).

Various cell types produce IL-4 and IL-13, including Th2 cells, mast cells, and basophils; they play an important role in Th2 inflammation, particularly in the pathogenesis of allergy, asthma, atopic dermatitis, and also inhibition of certain forms of autoimmunity (2). They have a similar three-dimensional structure and share receptor complexes (16). As a result, these two cytokines signal through common components; IL-13 binding causes activation of JAK1 and Tyk2, which in turn causes phosphorylation of cytoplasmic tyrosines in the IL-4R{alpha} chain. Crucially, this allows the recruitment of STAT6 to the receptor and subsequent phosphorylation/activation; STAT6 can then dimerize, translocate to the nucleus, and activate transcription of target genes (see Hershey (17) for comprehensive review). IL-4 and IL-13 therefore have overlapping but pleiotropic functions, which include enhancing B cell proliferation and isotype-switching, antagonizing the effects of IFN-{gamma}, inducing the differentiation of DC (in combination with GM-CSF), and affecting T cell proliferation and differentiation (for IL-4, but not IL-13). They can also act on nonhemopoietic cells, including endothelial cells and smooth muscle cells where IL-13 stimulation enhances the production of CXCL8, CCL2, and CCL5 (18, 19).

To elucidate the effects of IL-13 in the early stages of the differentiation pathway to an alternatively activated M{phi} phenotype, freshly isolated human monocytes were stimulated with IL-13, and their transcriptional profile was investigated using high-density oligonucleotide microarray analysis.

Validation of this analysis was provided by the identification of genes such as mannose receptor (MRC1), CD23, and 15-lipoxygenase (ALOX15), which are known to be modulated by IL-13 in monocytes/M{phi} (12, 20, 21). Microarray analysis highlighted the regulation of many new genes involved in Ag presentation, host-pathogen interactions, and also lipid metabolism, including CD1b/c/e, TLR1, and DHCR24. The most striking results were those showing a very complex regulation of the components of the IL-1 system. At least six different genes involved in IL-1{beta} production, signal transduction, and biological activity were regulated, with some of them not previously identified as genes associated with the alternative activated phenotype.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Cell purification and culture

Monocytes were isolated from buffy coats from healthy donors, obtained through the Centro Trasfusionale (Ospedale Sacco, Milan, Italy). Blood was washed with pyrogen-free saline (SALF) and spun at 250 x g for 10 min to remove plasma and platelets, then loaded on Ficoll and spun at 600 x g for 25 min. The PBMC layer was collected, the cells were washed twice in saline and then resuspended in 285-mOsm RPMI 1640 (Biochrom) supplemented with 10% FCS (HyClone Laboratories). Monocytes were then isolated by loading on 46% (v/v) iso-osmotic Percoll and spinning at 750 x g for 25 min. The obtained monocyte population was ~65% pure according to flow cytometry; monocytes were further purified using a MACS monocyte isolation kit (Miltenyi Biotec), according to the manufacturer’s instructions. The cells obtained after MACS were >95% pure according to flow cytometry; briefly, 1 x 105 cells were washed in PBS supplemented with 1% BSA and 0.01% NaN3 (FACS buffer). Cells were then resuspended in 100 µl of FACS buffer, and 10 µg of human IgG (Sigma-Aldrich) was added to block FcRs. After 15-min incubation at room temperature, FITC-conjugated anti-CD14 Ab or IgG1 isotype control Ab (both from Serotec) was added to a concentration of 10 µg/ml, and the cells were incubated for 30 min on ice. Cells were then washed twice in FACS buffer before analysis on a FACSCalibur flow cytometer (BD Biosciences) using CellQuest software.

Five milliliters of pure monocytes were seeded in nonadherent hydrophobic petriperm dishes (Sigma-Aldrich) at a concentration of 2 x 106 cells/ml in RPMI 1640/10% FCS and incubated at 37°C for 1 h. The cells were then stimulated with IL-13 at a concentration of 20 ng/ml for 2 or 8 h. Human IL-13 was a kind gift from Dr. A. Minty (Sanofi Elf Bio Recherches, Labège, France). In some experiments, LPS from Escherichia coli strain 055:B5 (Difco Laboratories) was added at a concentration of 100 ng/ml for the final 4 h of culture.

RNA and cRNA synthesis

cRNA was generated according to the instructions provided by Affymetrix. Total RNA was extracted from 1 x 107 monocytes using TRIzol (Invitrogen Life Technologies), according to the manufacturer’s instructions, then DNase-treated using the DNase I Amplification-Grade kit (Invitrogen Life Technologies). The volume of DNase-treated total RNA was adjusted to 100 µl, then further purified using the RNeasy Mini-kit (Qiagen), precipitated using a standard ethanol precipitation, and resuspended in diethyl pyrocarbonate-treated H2O. Six micrograms of total RNA were used to synthesize double-stranded cDNA using the Superscript Double-Stranded cDNA Synthesis kit (Invitrogen Life Technologies) according to themanufacturer’s instructions, except that a T7-(dT)24 oligonucleotide (5'-GGCCAGTGAATTGTAATACGACTCACTATAGGGAGGCGGT24-3'; Genset) was used in place of the oligo provided with the kit. The cDNA was purified using a standard phenol-chloroform extraction followed by ethanol precipitation. cRNA was then synthesized using the BioArray High Efficiency RNA Transcript Labeling kit (Enzo Life Sciences), cleaned up using the Qiagen RNeasy Mini Kit and ethanol precipitation, and fragmented, before microarray analysis.

Affymetrix genechip analysis and data mining

Fragmented cRNA was hybridized to Affymetrix HG-U133A genechips (Affymetrix), and then washed and scanned, according to the manufacturer’s guidelines. These genechips contain 22,283 probe sets, corresponding to almost 15,000 genes. Monocytes from six individual donors were analyzed after 8-h incubation in the presence or absence of IL-13 (20 ng/ml). Monocytes from three of these donors were also analyzed after 2-h stimulation with IL-13. To define the IL-13-dependent transcriptional profile, expression measures were computed using robust multiarray average (RMA) after quantiles normalization of the probe level data (22, 23). Differential expression was assessed by t test (p < 0.05), and type II error was controlled by applying a false detection rate (FDR) function (24). All of the above computations were conducted using the R statistics programming environment available at <www.r-project.org>. Genes were considered to be differentially regulated in IL-13-stimulated cells compared with control cells if they had a log intensity average difference of 1.0, corresponding to a fold change of 2.0. Gene Ontology (GO) data mining (25) for biological process at level 3, and Expression Analysis Systematic Explorer (EASE) biological theme analysis (26) were conducted online at <http://david.niaid.nih.gov> using DAVID (27). Identification of potential transcription factor (TF) binding sites was performed using Toucan (28). Briefly, for each gene, the genomic sequence comprising 2000 bp upstream of, and 200 bp within the first exon was obtained from Ensembl. These sequences were then examined using the MotifScanner function in Toucan, using the Transfac 6.0 public Vertebrates TF matrix (29), with a stringent priority level of 0.1 and a Human Third Order background model.

Real-time PCR

RNA was purified as described above, and 2 µg were used to synthesize single-stranded cDNA using the Superscript First-Strand Synthesis System for RT-PCR (Invitrogen Life Technologies), according to the manufacturer’s instructions. Real-time quantitative RT-PCR was then performed using the SYBR Green PCR Master Mix (Applied Biosystems) with forward and reverse primers at a final concentration of 300 nM (GAPDH primers were used at 200 nM), in a sample volume of 25 µl. Primers for caspase 1 and CX3CR1 were a kind gift from P. Perrier and F. Marchesi, respectively (both from Istituto Mario Negri, Milan, Italy). The remaining primers were designed using Primer 3.0 software (30) from mRNA sequences submitted to GenBank, and are listed in Table I. PCR was conducted using a GeneAmp 5700 Sequence Detection System (Applied Biosystems) under the following cycling conditions: 2 min at 50°C (one cycle), 10 min at 95°C (one cycle), 15 s at 95°C, and 1 min at 60°C (40 cycles). For each gene (performed in duplicate for each sample), cycle threshold (Ct) values were determined from the linear region of the amplification plot and normalized by subtraction of the Ct value for GAPDH (generating a {Delta}Ct value). The response to IL-13 was determined by subtraction of the {Delta}Ct value for the time-matched control from the {Delta}Ct value for the IL-13-stimulated sample ({Delta}{Delta}Ct value). Fold change was subsequently calculated using the formula 2{Delta}{Delta}Ct (where {Delta}{Delta}Ct was converted to an absolute value), and down-regulated genes were arbitrarily assigned a negative fold change. For statistical analysis, a two-tailed paired t test was performed comparing the {Delta}Ct values for IL-13-stimulated and control samples. Between three and eight donors were investigated.


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  		Table I. Primer pairs used for real-time quantitative RT-PCRa

 
ELISA

The concentration of human IL-1{beta} in cell culture supernatants was measured using a Human IL-1{beta} colorimetric ELISA (Endogen) according to the manufacturer’s instructions.

Caspase 1 assays

Relative levels of active caspase 1 activity were determined by flow cytometry using FAM-fluorochrome inhibitor of caspases (FLICA) reagent (Immunochemistry Technologies) according to the manufacturer’s instructions. Briefly, 300 µl of monocytes were incubated with the FAM-YVAD-fluoromethylketone reagent for 1 h at 37°C. The FAM-FLICA reagent is cell permeable and binds covalently to active intracellular caspase 1. Unbound reagent was removed by two washes in wash buffer. The cells were then resuspended in 300 µl of wash buffer and propidium iodide was added, to distinguish dead cells. The cells were then analyzed on a FACSCalibur flow cytometer, gating on the live cells, and measuring the fluorescence due to the presence of FAM-FLICA bound to caspase 1.

Western blotting

Monocytes were cultured as described above. After 8 h of culture, 1-ml aliquots were removed onto ice and centrifuged at 13,000 rpm for 10 s in a microfuge. The cell pellets were washed twice with 1 ml of ice-cold PBS containing 20 mM NaF (0.5 M stock; Sigma-Aldrich), 1 mM Na3VO4 (0.2 M stock; Sigma-Aldrich), and {beta}-glycerophosphate (0.5 M stock; Sigma-Aldrich). The cells were then lysed in lysis buffer, containing 50 mM Tris-HCl (pH 8.0), 1% Triton X-100, 100 mM NaCl, 1 mM MgCl2, 1 mM Na3VO4, 20 mM NaF, 1 mM {beta}-glycerophosphate, 25 µg/ml aprotinin, 25 µg/ml pepstatin A, and 50 µg/ml leupeptin (all from Sigma-Aldrich). Then, 100 µl of ice-cold lysis buffer was added to each aliquot of 2 x 106 cells. Cells were lysed by pipetting up and down, and then genomic DNA was sheared by repeatedly passing the lysate through a 25-gauge needle connected to a 1-ml syringe. The protein concentration of each lysate was determined using a Micro BCA Protein Assay Reagent kit (Pierce) in microplate format, according to the manufacturer’s instructions. Lysates were adjusted to 1 µg/µl and stored at –70°C.

A total of 15 µg of each lysate were run on 12% SDS-acrylamide gels, and then the protein was transferred to nitrocellulose membrane (Amersham Biosciences) using the Mini Trans-Blot Electrophoretic Transfer Cell (Bio-Rad), according to the manufacturer’s instructions. The membrane was probed for IL-1{beta} using an anti-human IL-1{beta} Ab (Cell Signaling Technology) followed by an HRP-conjugated donkey anti-rabbit secondary Ab (Amersham Biosciences), according to the manufacturer’s instructions. Specific Ab binding was detected using ECL Western Blotting Detection Reagents (Amersham Biosciences) followed by exposure to x-ray film.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Monocyte transcriptional profile after IL-13 stimulation

Freshly isolated human monocytes (>95% pure by flow cytometry) were stimulated with 20 ng/ml IL-13 for 2 or 8 h; this concentration of IL-13 was previously shown to be optimal for stimulating a variety of responses in human monocytes (31). The transcriptional profile was then determined by microarray analysis using Affymetrix HG-U133A genechips (consisting of 22,283 probe sets, corresponding to ~15,000 genes); three donors were analyzed at the 2-h time point, and six donors were analyzed at the 8-h time point, using 8-h unstimulated monocytes as the baseline control.

IL-13 had a potent effect on the monocyte transcriptional profile: after 8-h stimulation, 442 regulated genes were identified following the initial RMA analysis (see additional information at <www.marionegri.it/profiles>), and this was reduced to 142 regulated genes after restricting the profile to those genes with a fold change of ≥2 (Table II). Of the 142 genes affected after 8-h IL-13 stimulation, 85 were up-regulated (with a maximum fold change of 22.6) and 57 were down-regulated (with a maximum fold change of 11.3). The majority of these genes have been characterized; only 11 genes were unidentified or hypothetical. According to the microarray analysis, the maximally regulated genes were fatty acid binding protein 4 (FABP4; increased expression) and ADAM-like Decysin 1 (ADAMDEC1; decreased expression).


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  		Table II. List of genes regulated in human monocytes after 8-h stimulation with IL-13 (20 ng/ml)a

 

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  		Table IIA. Continues

 

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  		Table IIB. Continues

 
Many of the genes regulated after 8-h IL-13 stimulation have been previously identified as being regulated by IL-13 or IL-4 in monocytes/M{phi}, demonstrating the validity of our experimental protocol. These genes include mannose receptor (MRC1), CD23 (FCER2; FcR for IgE), CCL22 (also known as MDC), arachidonate 15-lipoxygenase (ALOX15), IL-1RII, and IL-1Ra (12, 20, 21, 31, 32, 33).

Two hours of IL-13 stimulation had a greater effect on the transcriptional profile, with 638 genes regulated with a fold change of >2 (435 genes up-regulated; 203 genes down-regulated). For the purposes of clarity, these genes are not described in detail in this paper, but the full list is freely available at <www.marionegri.it/profiles>. However, 70 of the genes regulated at 2 h (with a fold change >2) were also regulated at 8 h, as shown in Table II; an additional six genes had a fold change <2, whereas the remainder were unchanged at 2 h but regulated at 8 h.

Hierarchical clustering of the genes regulated at 8 h (including their observed expression at 2 h) using Euclidean distances after median centering of their eisen expression values, revealed six major clusters (Fig. 1). Genes in cluster 1 had high expression levels after 8-h IL-13 stimulation, compared with the global median expression; this cluster was further divided according to whether genes had low expression at 2 h (cluster 1A) or not (cluster 1B). Genes in cluster 2 had relatively low expression in the unstimulated cells, but higher expression after 2- and 8-h IL-13 stimulation; again, this cluster was further subdivided depending on the expression levels at 2 h. Genes in cluster 3 had high expression in unstimulated cells and low expression after 2- and 8-h IL-13 stimulation. Finally, cluster 4 genes had high expression in unstimulated cells and after 2-h IL-13 stimulation, followed by low expression after 8-h IL-13 stimulation.



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  		FIGURE 1. Hierarchical clustering (using Euclidean distances) of the median-centered eisen expression values. The 142 genes that were regulated after 8-h IL-13 stimulation were hierarchically clustered, including their observed expression at 2 h. Six major clusters were observed, with a similar pattern of regulation. Cluster 1A principally contained genes involved with lipid metabolism, whereas the remaining clusters were a mix of genes. Expression is indicated by a color scale from low (green) to high (red).

 
GO data mining for biological process (at level 3) suggests that the transcriptional profile induced by IL-13 is principally related to signal transduction, response to a biotic stimulus, and protein metabolism (Fig. 2). However, using the online version of the EASE (available at <http://david.niaid.nih.gov/david>), which performs a statistical analysis of gene categories in the gene list to find those categories that are the most overrepresented (and can therefore be described as "themes" of the gene list), reveals a trend toward immunity (e.g., inflammatory response, innate immune response, response to pest/pathogen/parasite, etc.), as might be expected of IL-13-regulated genes (Table III).



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  		FIGURE 2. GO data mining. The 142 regulated genes were characterized according to their biological process classification (at level 3) in the GO database (25 ). Thirty-three percent of the genes did not have a GO classification. The majority of the remaining genes were involved with signal transduction and response to a biotic stimulus.

 

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  		Table III. EASE overrepresentation analysis of the genes listed in Table IIa

 
It is clear from the gene list in Table II that there are several genes involved with the cell cycle or cell differentiation. These include ADAM-like decysin 1 (ADAMDEC1) whose expression is increased during the in vitro differentiation of monocytes into M{phi}, and further increased after classical LPS activation of these M{phi}, but which is not expressed in immature DC (34). IL-13 decreases the expression of this molecule in monocytes, which could promote differentiation toward a DC phenotype rather than a M{phi} phenotype. In contrast, Wnt5A is highly up-regulated by IL-13; this gene is important during hemopoiesis for controlling the phenotypic specialization of blood cells. Overexpression of Wnt5A in hemopoietic progenitor cells increases the proportion of erythrocytes and monocytes, while reducing the number of M{phi} (35). In (mature) monocytes, induction of this gene by IL-13 could therefore play an important role in driving the differentiation of monocytes toward a DC phenotype.

Many of the IL-13-regulated genes are enzymes or other molecules involved with metabolism, such as phosphofructokinase (PFKP) and adenosine deaminase (ADA). Of interest, "lipid metabolism" had a significant EASE score (Table III), and several of the enzymes in Table II appear to have a role in regulation of fatty acids and/or cholesterol biosynthesis (according to their GO), such as fatty acid desaturase 1 and 2 (FADS1/2), acyl-coenzyme A dehydrogenase (ACADVL), 24-dehydrocholesterol reductase (DHCR24), and sterol-C4-methyloxidase-like (SC4MOL). Also, the transporter molecule ABCA1 has a role in cholesterol transport (36); regulation of these genes may have implications for the pathogenesis of atherosclerosis and foam cell formation, where a role for IL-13 has been suggested (20). Moreover, the majority of the lipid metabolism-related genes are closely associated in cluster 1A (Fig. 1); this shows that their expression pattern in response to IL-13 is very similar, and may therefore be under the control of a common signaling pathway downstream of IL-13. Analysis of TF binding sites using Toucan (see Materials and Methods) reveals the significant overrepresentation of potential binding sites for the TF NF-Y in cluster 1A (data not shown); this molecule has been implicated in the regulation of other genes in cholesterol biosynthesis (37, 38).

As suggested by the EASE results, a significant proportion of the IL-13-regulated genes have immunological relevance, including complement component 3 (C3), CCL22 (31), CXCR2 (39), CXCR4, IL13R{alpha}1, IFNGR1, and IL3R{alpha} (40). This analysis did not reveal any regulation of cytokines such as TNF-{alpha}, TGF-{beta}, IL-1{beta}, or IL-6 (2). Of particular interest are the large number of pattern recognition receptors: some of these genes, including MRC1, CD14, and CD23 (FcER2), are known to be regulated by IL-13 (12, 21, 41); however, IL-13 also up-regulates three members of the CD1 family (CD1b, -c, and -e) and a C-type lectin (CLECSF6), while down-regulating another C-type lectin (CLECSF9) and TLR1. CLECSF6 has previously been shown to be up-regulated by IL-13 in neutrophils (42). CD1b, -c, -e, and CD23 are located very closely together in cluster 1B (Fig. 1), suggesting a similar pattern of up-regulation by IL-13. The increased expression of CD1 could be of considerable interest in terms of lipid and glycolipid Ag presentation to T cells. Moreover, ligands that are bound by MRC1 could be internalized to late endosomes for subsequent presentation by CD1b (13), as has been shown in DC. This will be the subject of further investigation in our laboratory.

Clearly therefore, the transcriptional profile has a range of genes including TF, cytokine and chemokines and/or their receptors, other cell surface molecules, enzymes, and signal transduction components. Several of these genes (distributed throughout the different clusters shown in Fig. 1) were chosen for analysis by real-time quantitative RT-PCR, to confirm the results of the microarray analysis.

Real-time PCR analysis of IL-13-regulated genes

Real-time PCR was used to verify the up- or down-regulation of selected genes, using the primer pairs shown in Table I. In addition, three genes of interest to our laboratory were included that were not revealed by the microarray analysis: CXCR1, CX3CR1, and MMP9. There was a good agreement between the real-time PCR data and the Affymetrix data (Fig. 3), with confirmation of the up- or down-regulation of each gene; these data also had a similar pattern to the clustering seen in Fig. 1. For many of the genes, the fold change was also of a comparable magnitude, although CD1c, Wnt5A, and CTNNAL1 showed a massive up-regulation according to real-time PCR. The regulation of either mRNA or protein for CXCR2, IL-1RI, IL-1RII, IL-1Ra, and PPAR{gamma} has previously been demonstrated after IL-4 or IL-13 stimulation of human monocytes or M{phi} (32, 33, 39, 43).



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  		FIGURE 3. Real-time quantitative RT-PCR for genes selected from the profile. Sixteen genes from the list in Table II (plus three additional genes that were not identified by microarray analysis) were analyzed by real-time PCR to confirm the genechip results ({cjs2108}, 2 h; {blacksquare}, 8 h). Down-regulated genes were arbitrarily assigned a negative value. For the genes marked with a number sign (#), the expression at 2 h was not determined. *, p < 0.05.

 
Of interest, CXCR1 and CX3CR1 showed significant up- and down-regulation respectively, although these genes were not identified by microarray analysis. MMP9 expression was also reduced, although this was not quite statistically significant (p = 0.073). These data demonstrate that microarrays may not always identify genes that are known to be regulated. The most likely explanation for this discrepancy is due to interindividual variability—human blood donors can have marked differences in their gene expression, which obviously makes it more beneficial to have larger sample sizes. There could also be a problem with either the probe sets on the genechip (lack of sensitivity or specificity) or the subsequent analysis, although an alternative approach to the analysis (using the proprietary Affymetrix Microarray Suite 5.0 software) did not identify these genes either. Real-time PCR for other genes that are not listed in Table II, such as CCR2 and p75 TNFR, validated that these genes are not regulated (data not shown).

The increased expression of CXCR1/2 by IL-13 has previously been demonstrated in our laboratory (39) and has implications for the control of monocyte migration in a variety of inflammatory situations. The IL-13-dependent down-regulation of the chemokine receptors CXCR4 and CX3CR1 in human monocytes is novel, and again may have important implications in pathology. Work by Fraticelli et al. (76) showed that CX3CL1 (fractalkine, the ligand for CX3CR1) is important in polarized Th1/Th2 responses. IL-4/IL-13 blocked the induction of this chemokine by endothelial cells, and Th2 cells were shown to have lower expression of CX3CR1 than Th1 cells. The reduction in CX3CR1 expression in monocytes by IL-13 may also contribute to Th1/Th2 polarization; the functional significance of this regulation is the topic of current investigations in our laboratory.

A reduction in the expression of caspase 1 after 8 h of IL-13 stimulation was also confirmed by real-time PCR. Caspase 1 is also known as the IL-1{beta}-converting enzyme (ICE), and is responsible for the proteolytic cleavage of pro-IL-1{beta} to its mature form (44, 45). Because regulation of caspase 1 could therefore modulate IL-1{beta} production in monocytes, we focused our attention on this gene.

Caspase 1 assay

According to the microarray analysis and real-time PCR, there was a ~3-fold down-regulation of caspase 1 mRNA after 2-h stimulation with IL-13 and a 5-fold down-regulation after 8 h. Therefore, we investigated whether the reduction in mRNA levels corresponded to a reduction in the level of active caspase 1, using a FAM-FLICA assay (see Materials and Methods). Caspase 1 exists as a 45-kDa precursor and must itself be proteolytically cleaved into an active heterodimer composed of a 10- and 20-kDa chain, before it can act on IL-1{beta} (see Ref.46 for review). Monocytes were stimulated for 4 h with IL-13, and then a further 4 h with the addition of LPS to induce active caspase 1; the cells were then stained with the FAM-FLICA reagent, and the level of active caspase 1 was determined by flow cytometry. As shown in Fig. 4, 100 ng/ml LPS alone caused an increase in caspase 1 activity compared with unstimulated control cells, as evaluated by an increase in mean channel fluorescence. Pretreatment of the cells with as little as 2 ng/ml IL-13 was sufficient to prevent the LPS-dependent increase in caspase 1 activity, suggesting that a reduction in mRNA levels has a subsequent effect on the capacity for generating active caspase 1.



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  		FIGURE 4. A, Caspase 1 activity in monocytes stimulated with LPS and/or IL-13. Monocytes were cultured for 8 h, in the presence or absence of IL-13 (at 2, 20, or 200 ng/ml). Caspase 1 activity was induced by the addition of LPS (100 ng/ml) for the final 4 h of culture, and the level of caspase 1 activity was measured by flow cytometry using FAM-FLICA reagent. LPS stimulation alone (gray shading) increased the level of caspase 1 activity relative to control cells or cells pretreated with IL-13 before LPS stimulation (black lines), as indicated. Results from one experiment are shown, representative of three independent experiments. B, Graphical representation of the mean results from the three independent experiments, showing the increase in caspase 1 activity relative to control cells and the abrogation of LPS-stimulated caspase 1 activation due to pretreatment with different concentrations of IL-13.

 
Reduced cleavage of pro-IL-1{beta} in IL-13-stimulated monocytes

Cell lysates from the above stimulated monocytes (4 h with or without IL-13 followed by 4 h with or without LPS) were probed for IL-1{beta} by Western blotting, while supernatants were collected for subsequent ELISA. As has been shown previously for IL-4/IL-13 (41, 47), we found that stimulation of monocytes with IL-13 caused a dose-dependent and significant reduction in LPS-induced IL-1{beta} concentration in cell culture supernatants (data not shown). Western analysis of 20 µg of cell lysate showed that at least part of the reduction is due to decreased processing of pro-IL-1{beta} (Fig. 5). In unstimulated control cells, no IL-1{beta} was detectable. But after LPS stimulation, there was detectable 31-kDa pro-IL-1{beta} and also mature 17-kDa IL-1{beta}, indicating that the proteolytic cleavage of IL-1{beta} was occurring. However, pretreatment of the cells with IL-13 reduced the ratio of mature IL-1{beta} to pro-IL-1{beta}, which corresponds with the deficiency in active caspase 1 and hence the capacity for proteolytic cleavage of pro-IL-1{beta}. Because IL-13 stimulation did not cause an accumulation of pro-IL-1{beta} (the levels of pro-IL-1{beta} were comparable regardless of IL-13 stimulation), it is possible that IL-13 also caused a decrease in IL-1{beta} translation (we did not see down-regulation of IL-1{beta} mRNA by microarray analysis), or that pro-IL-1{beta} was being secreted (48).



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  		FIGURE 5. A, Western blot analysis of intracellular IL-1{beta} protein. Monocytes were cultured as in Fig. 4, and cell lysates were prepared. Twenty micrograms of total protein were analyzed by Western blot for the presence of pro-IL-1{beta} and its proteolytically cleaved mature form. LPS alone resulted in the expression of pro-IL-1{beta} protein, and a significant proportion of this was processed to the mature form. Pretreatment with IL-13 did not prevent the expression of IL-1{beta} but did reduce the proportion of mature IL-1{beta}, suggesting a deficiency in proteolytic processing. B, Densitometric analysis of the bands shown in A, showing the clear reduction in the ratio of mature IL-1{beta} to pro-IL-1{beta}. Results are representative of two independent experiments.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
IL-13 is a prototypic Th2 cytokine mainly produced during the cellular or humoral immune response to parasitic and extracellular pathogens, and also during allergic reactions. In M{phi}, IL-13 and IL-4 can induce an alternative activated phenotype characterized by the up-regulation of various molecules including mannose receptor (MRC1) and MHC class II (see Refs.2 and 3 for recent review).

In this study, we investigated the effects of IL-13 on monocytes using Affymetrix microarray technology. To our knowledge, this is the first transcriptome analysis performed on this cell population after stimulation with this Th2 cytokine. After 8-h stimulation with IL-13, 142 genes were identified with a statistically significant difference in expression, and a fold change of >2. Our microarray analysis included many of the known genes that are up- or down-regulated by IL-13.

IL-13Rs can also be expressed by other cell types including endothelial cells, smooth muscle cells, and fibroblasts. A recent paper by Jinnin et al. (49) investigated the transcriptional profile induced by IL-13 in fibroblasts. They saw significant regulation of genes such as {alpha}2(I) collagen, IL-16, and proteinase-activated receptor 1, but their analysis did not identify any of the genes described in our study. We have also conducted real-time PCR analysis of several of the genes listed in Table I in HUVECs. The majority of the genes were either absent, or expressed at several orders of magnitude lower than in monocytes. However, expression of CXCR4, IL1R1, and IL1R2 was detectable at significant levels, and IL-13 stimulation resulted in up-regulation of all three genes (data not shown). IL-13 will likely regulate its target genes in a cell type-specific manner, although control of some genes such as IL1R1/2 may be comparable in different cell populations. Because STAT6 is important for downstream signaling in both hemopoietic and nonhemopoietic cells in response to IL-13 or IL-4, other signaling events must contribute to the observed differences both between IL-13 and IL-4, and between cell types. For example, previous studies have investigated the transcriptional profile induced by IL-4 in murine M{phi} (50, 51). Welch et al. (50) and Loke et al. (51) found IL-4 regulation of genes including MRC1 and Fc{gamma}RIII, but there are distinct differences from our profile. Both groups demonstrated up-regulation of Ym1 and arginase, yet neither of these genes was found in our study. Such differences reflect the fact that IL-4 and IL-13 are highly similar yet different molecules.

Comparison with a recent paper by Jung et al. (52) on the IL-10-induced gene expression profile in monocytes is also interesting. Their results show that IL-10 regulates some of the genes identified in our profile. IL-10 and IL-13 have a comparable effect on the expression of IL-1Ra and IL13R{alpha}1, but contrasting effects on CX3CR1, LILRB2, CD1e, and CD163. IL-10 bears some similarities to a Th2 cytokine and often has a similar expression pattern during an immune response, but these results demonstrate that, despite the apparent similarities, IL-10 and IL-13 have many opposing effects on monocytes.

GO data mining, and particularly EASE analysis, logically characterized the regulated genes as being involved with an inflammatory response. However, hierarchical clustering revealed a group of genes related to lipid metabolism and cholesterol biosynthesis. Combined with the observed up-regulation of MRC1, ALOX15, and PPAR{gamma}, plus the down-regulation of ABCA1, these genes may be of interest with respect to atherosclerosis and foam cell formation, where a role for IL-13 has been suggested but not categorically proven. Toucan analysis of TF binding sites suggests that the TF NF-Y may be involved with the regulation of these lipid metabolism genes; as well as regulating genes in the cholesterol biosynthesis pathway, this TF can also bind to the promoter for myeloperoxidase (MPO), another gene which has recently been implicated in atherosclerosis (53, 54).

Work by Huang et al. (43) has shown that IL-4 can up-regulate both PPAR{gamma} and ALOX15 in monocytes, and that ALOX15 can then generate ligands for PPAR{gamma} and hence coordinately mediate the induction of PPAR{gamma}-dependent genes. PPAR{gamma} induces the expression of MRC1 (55), and although there is currently no published data, it has been suggested that PPAR{gamma} may decrease the expression of CD163, another scavenger receptor that may be important in atherosclerosis (56, 57). Our results indicate that IL-13 may stimulate similar regulatory loops in monocytes, again with implications for disease (58).

As well as the effects on MRC1 and CD163, we also observed IL-13-dependent regulation of a number of other pattern recognition receptors. The up-regulation of CD1b/c/e may be of particular interest, because these molecules are involved with DC presentation of lipid and glycoprotein Ag to T cells (see Refs.59 and 60 for review). The early up-regulation of these genes in monocytes suggests that these cells may also be able to use CD1 for Ag presentation. Support for this suggestion is provided by the concomitant up-regulation of MRC1, which can endocytose Ag for eventual presentation by CD1b (13); maybe the other IL-13-regulated scavenger receptors can perform a similar function. Interestingly, TLR1 appears to be down-regulated by IL-13; this is a member of the TLR family, whose function is to recognize pathogens or their products and hence initiate innate immune responses (61, 62). A ligand for TLR1 alone has not been identified, but on heterodimerization with TLR2, the receptor complex can respond to microbial lipoproteins (63). IL-4 has been shown to down-regulate TLR2 in monocytes (64); this suggests that there may be functional significance for the decreased expression of TLR1 or TLR2 in response to Th2 cytokines. Regulation of these various pattern recognition receptors is currently being investigated in our laboratory.

The microarray analysis also revealed the up-regulation of SOCS1 and CISH; these molecules are members of the suppressors of cytokine signaling (SOCS) family, and are important for regulating the cellular response to cytokines. SOCS1 is induced by LPS and CpG in M{phi} and can inhibit IFN-{gamma} and IL-12 signaling (65). IL-4 and/or IL-13 up-regulate SOCS1 mRNA in a lung epithelial cell line and human keratinocytes, and SOCS1 can inhibit IL-4 signaling through the inhibition of JAKs (66, 67, 68, 69). CISH has been shown to negatively regulate IL-2 signaling in T cells, and it may also favor their differentiation into Th2 cells (65). Therefore, IL-13 up-regulation of SOCS1 could constitute a negative feedback loop, where SOCS1 expression inhibits further IL-13 signaling. In addition, SOCS1 or CISH could regulate the response to a variety of other cytokines and/or TLR ligands.

One of the most striking results from the microarray analysis was the regulation of genes involved with IL-1 signal transduction and biological activity. IL-1{beta} is a fundamentally important proinflammatory cytokine that is produced during infection, injury, and other pathological situations, and that can act on almost every type of cell (70). Because IL-1 is such a potent inflammatory mediator, its effects must be tightly regulated to avoid toxicity. The up-regulation of IL-1RI, IL-1RII, and IL-1Ra is one of the hallmarks of the alternatively activated M{phi} phenotype (2) and the increased expression of the IL-1 decoy receptor (IL-RII) and the receptor antagonist synergize to interfere with the effects of IL-1{beta} on these cells (71). In this study, we observed the down-regulation of caspase 1 mRNA. This enzyme is responsible for the proteolytic cleavage of pro-IL-1{beta} into its active mature form (44, 45). Our results show that pretreatment with IL-13 causes a reduction in caspase 1 activity and reduced processing of pro-IL-1{beta} after LPS stimulation; this may contribute to the lower concentration of IL-1{beta} seen in cell culture supernatants. The reduction in caspase 1 activity is expected to have similar effects on the processing of IL-18 (72). Of interest, real-time PCR analysis of MMP-9 showed a decrease in mRNA levels of this enzyme (although this was not seen by microarray analysis), which will be confirmed in future work. MMP-9 can also process pro-IL-1{beta} to mature IL-1{beta} in a caspase-independent pathway (73), suggesting a potential role for this enzyme in IL-1{beta} regulation by IL-13. PPAR{gamma} has been shown to negatively regulate MMP-9 activity in M{phi} (74). Moreover, PPAR{gamma} can inhibit the production of IL-1{beta} as well (75). We also have some preliminary data that IL-13 can decrease the expression of Pellino 1. This protein is required for IL-1{beta}-mediated signaling through IRAK1, IRAK4, and TRAF6; its down-regulation could therefore impede IL-1{beta} signaling.

In conclusion, we have provided the first transcriptome analysis of human monocytes after stimulation with IL-13. Many characteristic markers of alternatively activated M{phi} were seen in these cells, plus a variety of highly interesting novel IL-13-regulated genes. These included CD1, TLR1, and SOCS1, plus various components of the IL-1 system. Taken together, our microarray data outline the complex biological system required for the tight control of IL-1{beta} production and response. IL-13 stimulation leads to a decrease in caspase 1 activity, which consequently limits the production of mature IL-1{beta}. Meanwhile, increased expression of IL-1RII and IL-1Ra can negatively regulate the response to extracellular IL-1{beta}. Clearly, IL-1{beta} response and production is rigidly controlled in monocytes, and this will have a significant impact in the surrounding microenvironment; IL-13 will drive the alternative activation of monocyte/M{phi} and the reduced response to IL-1{beta} will potentiate this effect.


   Footnotes
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 C.J.S. was supported by a Marie Curie Fellowship from the European Community Human Potential Programme under Contract No. HPMF-CT-2001-01410. We also thank Associazione Italiana per la Ricerca sul Cancro and Ministero dell’Istruzione Università e Ricerca (cofin 2002) for financial support. Back

2 Current address: Centre for Respiratory Research, University College London, Rayne Institute, London, U.K. Back

3 Address correspondence and reprint requests to Dr. Silvano Sozzani, Section of General Pathology and Immunology, University of Brescia, viale Europa 11, 25123 Brescia, Italy. E-mail address: sozzani{at}med.unibs.it Back

4 Abbreviations used in this paper: M{phi}, macrophage; TF, transcription factor; Ct, cycle threshold; DC, dendritic cell; GO, Gene Ontology; EASE, Expression Analysis Systematic Explorer; FLICA, fluorochrome inhibitor of caspases. Back

Received for publication May 4, 2004. Accepted for publication October 14, 2004.


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