Shaping Gene Expression in Activated and Resting Primary Macrophages by IL-10

Roland Lang, Divyen Patel, John J. Morris, Robert L. Rutschman and Peter J. Murray
J Immunol September 1, 2002, 169 (5) 2253-2263; DOI: https://doi.org/10.4049/jimmunol.169.5.2253

Abstract

IL-10 regulates inflammation by reducing cytokine and chemokine production from activated macrophages. We performed microarray experiments to identify possible effector molecules of IL-10 and to investigate the global effect of IL-10 on the transcriptional response induced in LPS-activated macrophages. To exclude background effects of endogenous IL-10, macrophages from IL-10-deficient mice were used. IL-10 up-regulated expression of a small number of genes (26 and 37 after 45 min and 3 h, respectively), including newly identified and previously documented targets such as suppressor of cytokine signaling-3 and IL-1 receptor antagonist. However, the activation program triggered by LPS was profoundly affected by IL-10. IL-10 repressed 62 and further increased 15 of 259 LPS-induced genes. For all genes examined, the effects of IL-10 were determined to be STAT3-dependent. These results suggest that IL-10 regulates STAT3-dependent pathways that selectively target a broad component of LPS-induced genes at the mRNA level.

Interleukin-10 is an essential anti-inflammatory cytokine produced primarily from T cells and activated macrophages. IL-10 is capable of blocking or reducing the output of numerous proinflammatory agents from macrophages including cytokines such as TNF-α, IL-6, and IL-12, chemokines, and prostaglandins via blocking cyclooxygenase 2 expression (1, 2). Because of these broad effects, IL-10 has elicited considerable clinical interest to treat chronic inflammatory conditions such as Crohn’s disease (3) and hepatitis C-induced fibrosis (4).

No consensus has emerged as to how IL-10 inhibits production of cytokines and chemokines from macrophages. Inhibition of TNF-α production by IL-10, for example, has been attributed to effects on NF-κB activation (5), mitogen-activated protein kinase (MAPK)4 signaling pathways (6), rate of transcription (7), mRNA stability (8), translational efficiency (6), cleavage from the membrane, and uptake via TNF receptors (9) (for reviews, see Refs. 1 and 2). Also, conflicting results have been reported for most of these effects. In contrast, genetic and biochemical analysis has elucidated the membrane proximal events of IL-10 signaling. The functional IL-10R consists of the ligand binding IL-10R1 and the accessory subunit IL-10R2 (1, 2). Although IL-10R2 is expressed on most cells and tissues, IL-10R1 is expressed on hemopoietic cells and up-regulated on macrophages upon activation (1, 2). This fact, combined with genetic evidence from a variety of animal model systems, supports the notion that macrophages are the primary target of IL-10 (10, 11). Binding of IL-10 to its receptor initiates signaling via the Janus kinase-STAT pathway. Limited studies using fetal liver-derived Janus kinase 1-deficient macrophages (12) suggest this kinase is essential for early IL-10 signaling. STAT3 plays a pivotal role because the conditional inactivation of STAT3 in myeloid lineage cells results in abrogated IL-10 responses of macrophages and development of chronic enterocolitis similar to IL-10-deficient (IL-10−/−) mice (11).

It is not known how IL-10 attenuates macrophage activation downstream of STAT3. Experimental evidence suggests that new protein synthesis is required for IL-10 to inhibit LPS-induced cytokine production, since IL-10 does not appear to inhibit IL-12 p40 or TNF-α expression in LPS-stimulated macrophages when cycloheximide is added (8, 13). To date, few genes have been described to be induced by IL-10. We reasoned that a gene expression screen for IL-10-induced genes in macrophages should identify a range of targets potentially involved in deactivation of macrophages. We took advantage of macrophages from mice deficient in IL-10 or STAT3 and microarray techniques to identify and validate genes induced and repressed by IL-10 in resting and activated macrophages.

Materials and Methods

Reagents, mice, and macrophages

IL-10 and IL-4 were purchased from BD PharMingen (San Diego, CA), LPS was obtained from Sigma-Aldrich (St. Louis, MO). IL-10−/− mice (14) on a C57BL/6 background and controls were purchased from The Jackson Laboratory (Bar Harbor, ME). STAT3flox/− and LysMcre breeding pairs were a gift from I. Förster (Technical University of Munich, Munich, Germany). Peritoneal-derived macrophages (PDM) and bone marrow-derived macrophages (BMDM) were isolated as previously described (10). Detection of IL-10 and TNF-α in culture supernatants was by ELISA using Ab pairs from BD PharMingen.

Affymetrix gene chip analysis

IL-10−/− BMDM were stimulated with IL-10 (10 ng/ml), LPS (100 ng/ml), or IL-10 + LPS for 45 min or 3 h. For both timepoints, two completely independent experiments were performed. Total RNA was prepared using TRIzol (Life Technologies, Gaithersburg, MD), processed, and hybridized to MG-U74Av2 gene chips according to Affymetrix protocols (Santa Clara, CA). Chips were scanned and analyzed using Affymetrix Microarray Suitev4.0 software. Sample loading and variations in staining were standardized by scaling the average of the fluorescent intensities of all genes on an array to constant target intensity (2500) for all arrays used. The signal intensity for each gene was calculated as the average intensity difference, represented by (Σ(PM−MM)/(number of probe pairs)), where PM and MM denote perfect-match and mismatch probes.

Data analysis

Data sets of 12,488 probe sets per array were compared using Microsoft Excel (Microsoft, Redmond, WA) and Spotfire software. To avoid negative ratios, average intensity differences < 5 were first set to 5 (15). Data were normalized by mean using the untreated sample as the baseline within each experiment. To identify differentially expressed genes, we excluded all genes from the analysis that were scored absent in the test sample (for up-regulated genes) or absent in the baseline sample (for down-regulated genes) in one or both experiments. Fold changes were calculated separately for both experiments as the ratio of normalized average intensity difference (test sample) divided by normalized average intensity difference (baseline sample). Thresholds were set for fold change (2-fold and greater unless otherwise indicated) and absolute difference (at least 500) between normalized average intensity differences. Consistency between experiments varied between samples depending on treatment and timepoint. For example, of the genes induced >3-fold by IL-10 in the first experiment, 50.0% for the 45 min and 55.6% for the 3 h timepoint were up-regulated at least 2-fold in the second experiment. When LPS treatment was compared with untreated, the corresponding numbers were 87.7 and 78.0%, respectively. To minimize the number of false-positives, only those genes that reproducibly met all the thresholds described above in both independent experiments were considered differentially expressed.

Northern blotting and real-time quantitative RT-PCR

For Northern analysis, 10–15 μg total RNA were separated on 1% formaldehyde-agarose gels and blotted onto Hybond N (Amersham, Piscataway, NJ). Probes were prepared from plasmids containing either full-length cDNAs (IL-12p40, GAPDH, IL-1R antagonist (IL-1ra), suppressor of cytokine signaling (SOCS)3, junB, growth arrest and DNA damage (GADD)45γ, GADD45α) or expressed sequence tags (ESTs) (NFIL-3, JE/monocyte chemoattractant protein (MCP)-1, tumor progression locus (Tpl)-2). For real-time quantitative RT-PCR, 1 μg of total RNA was reverse-transcribed using Superscript II (Life Technologies) and a mix of random hexamer and oligo(dT) primers. Primers were designed using PrimerExpress software (Applied Biosystems, Foster City, CA). For β-actin, TNF-α, arginase-1 and arginase-2, internal TaqMan probes were designed and included in the PCR. Sequences of primers and probes are available from the authors upon request. For all other target genes, the SYBR-green master mix was used to detect accumulation of PCR product during cycling on the SDS7700 (Applied Biosystems). Expression of target genes was normalized to β-actin and displayed as fold-change relative to the untreated 45-min sample used as the calibrator (set to 1).

Results

Choice of IL-10−/− BMDM as experimental system

We reasoned that experimental parameters, especially the choice of macrophage type and timepoints after stimulation, would be critical determinants of the results obtained by gene expression profiling. We analyzed the influence of these variables on inhibition of TNF-α production by IL-10 to establish conditions optimal to identify IL-10-induced genes and investigate its overall impact on the transcriptional response to LPS. In response to LPS, both BMDM and PDM rapidly produced TNF-α that was inhibited by IL-10 as expected (Fig. 1⇓). However, PDM made more TNF-α and showed a stronger inhibitory effect of IL-10. This difference was inversely correlated with much higher production of IL-10 in BMDM, suggesting that endogenous IL-10 blunted TNF-α production. We concluded that a system devoid of endogenous IL-10 would be advantageous for uncovering the full spectrum of IL-10-induced changes in gene expression. BMDM from IL-10−/− mice produced high amounts of TNF-α and were fully responsive to inhibition by IL-10. TNF-α production was down-regulated by IL-10 as early as 1 h after stimulation, but this effect was increased at 2–4 h. Therefore, we chose two timepoints for global expression profiling. After 45 min, mRNAs encoding IL-10-induced inhibitors of inflammatory responses should be present at detectable levels. A timepoint of 3 h was chosen to visualize later IL-10-induced differences in the transcriptional response to LPS. This later timepoint is expected to contain both directly and indirectly IL-10-induced genes that may play a role in the anti-inflammatory effects of this cytokine.

FIGURE 1.
FIGURE 1.

Inverse correlation between TNF-α and IL-10 production by PDM and BMDM. IL-10 (10 ng/ml) was added (□) or not (▪) to macrophages, followed by stimulation with LPS (100 ng/ml) for the indicated time. Cytokine levels in the supernatant were measured by ELISA. In the case of TNF-α production, similar results were obtained when brefeldin A-treated macrophages were analyzed for accumulation of intracellular cytokine by flow cytometry (data not shown).

Changes in gene expression induced by IL-10 in resting and activated macrophages

Stimulation with LPS induced a >2-fold induction of 149 genes after 45 min, and of 402 genes after 3 h, whereas 40 and 752 genes were repressed >2-fold by LPS at these timepoints (Fig. 2⇓). This substantial reprogramming of gene expression is consistent with other studies examining the impact of Toll-like receptor (TLR) ligands and pathogens on the macrophage transcriptome (16, 17, 18). In contrast, treatment with IL-10 induced 26 and 37 and repressed 25 and 22 genes >2-fold after 45 min and 3 h, respectively (Fig. 2⇓). A comparison of gene expression profiles in macrophages treated with LPS or IL-10 + LPS showed few differences after 45 min, but after 3 h the expression of 194 genes differed >2-fold (125 induced, 69 repressed by addition of IL-10) (Fig. 2⇓).

FIGURE 2.
FIGURE 2.

Time-dependent changes in gene expression induced by IL-10 and/or LPS. IL-10−/− BMDM were left untreated or stimulated with IL-10 and/or LPS for 45 min (upper panels) and 3 h (lower panels). RNA was prepared and processed for hybridization to MG-U74Av2 microarrays. Data were analyzed with Spotfire software, using the algorithm described in Materials and Methods. Genes that are induced >2-fold are shown in red, while those repressed >1.5-fold appear green. For each comparison, the number of genes induced >2/>3/>5-fold is presented in the upper left corner and the number of genes repressed >1.5/>2/>3-fold is presented in the lower right corner.

Of the 259 genes induced >3-fold by LPS after 3 h, 62 were repressed at least 1.5-fold by IL-10, whereas 15 genes were further up-regulated by IL-10 (Fig. 3⇓). As expected, a number of cytokines and chemokines previously described to be down-regulated by IL-10 (1, 2) were repressed in the microarray analysis confirming the robustness of this system. In addition, many transcripts belonging to various functional categories were identified as suppressed by IL-10 for the first time (Fig. 3⇓). It should be noted that 104 of the 259 LPS-induced genes were not regulated by IL-10 in both independent experiments.

FIGURE 3.
FIGURE 3.

Effect of IL-10 on LPS-induced genes. The 259 genes induced >3-fold by LPS compared with untreated macrophages in two independent experiments are displayed in the scatter plot to analyze changes in expression induced by treatment with IL-10 + LPS compared with LPS alone. Genes that are further induced >2-fold by the addition of IL-10 are shown as red squares, ones that are repressed >1.5-fold as green squares. These remaining genes were grouped into four categories as shown excluding 14 ESTs. Fold change values were obtained by dividing mean average differences (from two experiments) of IL-10 + LPS-treated by LPS sample (for induction by IL-10) and of LPS treated by IL-10 + LPS-treated sample (for repression by IL-10).

Genes and ESTs induced by IL-10 in resting and LPS-activated macrophages at 45 min are listed in Table I⇓. Results from the 3 h timepoints are listed in Table II⇓. Of the known target genes of IL-10 (1, 2), a significant fraction was confirmed in the microarray analysis including IL-1ra, CD32, CCR5, CCR1, scavenger receptor, and arginase-2. Some genes reported to be induced by IL-10 were not confirmed because they were not represented on the microarray (tissue inhibitor of metalloproteinase 1), not regulated (CD14, TNFR2, CD16, and CD64), or did not pass one or more of the thresholds in the stringent analysis criteria (p19INK4D, fMLPR). One of the genes most strongly induced by IL-10 was SOCS3, which has been reported as a target gene common to IL-10 and LPS, and implicated in inhibition of macrophage responses to IFN-γ (19, 20, 21). Around half of the genes induced by IL-10 were independently up-regulated in response to LPS (Table I⇓). For some of these genes, the combination of IL-10 and LPS resulted in synergistic induction (IL-1ra, Bcl-3, metallothionein-2, NFIL-3). Some genes were up-regulated specifically by IL-10 (e.g., GADD45γ, connexin 43, CCAAT/enhancer binding protein (C/EBP) δ, IL-4Rα) or the combination of IL-10 + LPS, but not by LPS (e.g., B-ATF) (Table I⇓). Independent confirmation of the results was obtained by Northern analysis or real-time quantitative RT-PCR for a subset of 15 genes scored as induced by the microarray analysis (Fig. 4⇓).

FIGURE 4.
FIGURE 4.

Validation of differential gene expression induced by IL-10 and/or LPS by Northern analysis and real-time quantitative RT-PCR. IL-10−/− BMDM were stimulated for 45 min and 3 h as indicated, followed by preparation of RNA. Northern blotting (A) and real-time quantitative RT-PCR (B) were done as described in Materials and Methods. Data are mean + SD of duplicate samples. Note the differing scales of the ordinate in each case.

View this table:
Table I.

Genes induced after 45 min by IL-10 in resting and LPS-stimulated macrophagesa

View this table:
Table II.

Genes induced after 3 h by IL-10 in resting and LPS-stimulated macrophagesa

View this table:
Table IIA.

Continued

View this table:
Table IIB.

Continued

One of the longer-term goals of this work is to identify molecular mediators of the attenuating effect IL-10 has on macrophages. In addition to SOCS3 and IL-1ra, both previously implicated in inhibition of macrophage activation, several of the target genes of IL-10 identified in this study could play a role in macrophage deactivation. Previous studies suggest IL-10 may regulate NF-κB and MAPK pathways, both essential for the initiation and propagation of proinflammatory gene expression (5, 6). We found several genes regulated by IL-10 that have been implicated in controlling NF-κB activation, such as metallothionein-2 (22) and Bcl-3 (23). Other IL-10 targets are involved in MAPK pathway regulation, e.g., GADD45γ (24) and Tpl-2, a MAPK kinase kinase (25) that can also activate IκB kinases (26). Mice deficient in Tpl-2 have a selective defect in TNF-α production due to impaired nucleocytoplasmic transport of the TNF-α mRNA (27). Because IL-10 inhibits TNF-α production, it is not clear whether induction of Tpl-2 by IL-10 is related to the anti-inflammatory effect of IL-10. To resolve this question, it will be important to test macrophages from mice lacking Tpl-2 for IL-10-induced deactivation. Further, several genes for transcriptional regulators were also induced by IL-10. One example of this group is the basic region leucine zipper transcription factor NFIL-3 that can function as transcriptional activator (28) or repressor (29).

STAT3 dependence of gene induction and repression by IL-10

Macrophages deficient in STAT3 are hyperresponsive to LPS and fail to respond to IL-10 with down-regulation of cytokines and inhibition of proliferation (11). To determine whether STAT3 is required for the induction and repression of the IL-10-dependent target genes described in this study, we used BMDM deficient in STAT3 (11). Expression of selected genes was analyzed by Northern blotting (Fig. 5⇓A) or real-time quantitative RT-PCR (Fig. 5⇓B). Inhibition by IL-10 of LPS-induced expression of IL-12 p40, TNF-α, and JE/MCP-1 was dependent on functional STAT3. The reduced levels of these mRNAs in the LPS-stimulated wild-type BMDM compared with IL-10−/− and STAT3−/− BMDM illustrates the attenuation of inflammatory responses by endogenous IL-10. For the IL-10-induced targets identified in this study including Tpl-2, NFIL-3, GADD45γ, IL-1ra, α1-microglobulin/bikunin precursor (AMBP), protein C receptor, MT-2, and B-ATF, the absence of STAT3 completely abrogated inducibility by IL-10 and reduced induction of IL-4Rα, Bcl-3, and connexin 43 mRNAs (Fig. 5⇓). This side-by-side comparison of wild-type macrophages with cells incapable of producing or responding to IL-10 also revealed that the expression of Tpl-2, AMBP, IL-4Rα, and B-ATF after stimulation with LPS is mediated indirectly by IL-10 or other factors signaling via STAT3 (Fig. 5⇓).

FIGURE 5.
FIGURE 5.

Role of STAT3 in the regulation of selected target genes by IL-10 and LPS. BMDM from IL-10−/−, STAT3flox/− LysMcre and STAT3+/+ LysMcre mice were stimulated for 2 h with IL-10 (10 ng/ml) and/or LPS (100 ng/ml), followed by preparation of RNA. Samples were analyzed by Northern blotting (A) or real-time RT-PCR (B) as described in Materials and Methods. Data are mean + SD of duplicate samples.

Up-regulation of IL-4Rα by IL-10 correlates with increased IL-4-dependent expression of arginase-1 (Fig. 6⇓)

FIGURE 6.
FIGURE 6.

IL-10- and LPS-induced changes in IL-4Rα expression correlate with inducibility of arginase-1 expression by IL-4. IL-10−/− BMDM were pretreated with IL-10 and/or LPS for 30 min, followed by addition of IL-4 (1 ng/ml) (▪) or media (▦). Total RNA was prepared 3 h and 8 h after addition of IL-4. After reverse transcription, cDNA was subjected to real-time quantitative RT-PCR for β-actin, IL-4Rα, and arginase-1. Fold changes relative to the 8 h media sample were calculated as stated in Materials and Methods. Data for IL-4Rα and arginase-1expression are from 3 and 8 h timepoints, respectively. Shown are mean + SD of duplicate samples.

The finding of increased IL-4Rα expression in macrophages treated with IL-10 (Tables I⇑ and II⇑, Figs. 4⇑ and 5⇑), suggested an enhanced sensitivity to IL-4 as a functional consequence of exposure to IL-10. Importantly, both cytokines are known to promote “alternative activation” of macrophages, a functional state characterized by high phagocytic capacity but a reduced ability to kill pathogens (30). A hallmark of “alternative activation” is high arginase activity, which competes with inducible NO synthase for l-arginine, the common substrate of both enzymes (31, 32), and can be due to the expression of either one of two isoforms. Arginase-2 was shown to be induced by LPS (33), and we found in this study that IL-10 synergized with LPS in increasing arginase-2 expression (Fig. 4⇑, Table II⇑). Expression of arginase-1 is induced by the Th2 cytokines IL-4 and IL-13 (34) in a STAT6-dependent manner (32). IL-10 strongly synergizes with IL-4 to induce arginase-1 (35), but the mechanistic basis for this effect has been unknown. Therefore, we evaluated whether the magnitude of arginase-1 induction after IL-4 stimulation is linked to the IL-10-mediated increase in IL-4Rα expression we observed in the array analysis. IL-4 strongly induced arginase-1 expression, which was further increased 10-fold by addition of IL-10 (Fig. 6⇑), correlating with the increased levels of IL-4Rα in macrophages treated with IL-10 alone or in combination with IL-4. In contrast, LPS down-regulated IL-4Rα expression and potently inhibited expression of arginase-1 in response to IL-4 (Fig. 6⇑). Combined addition of IL-10 and LPS restored high level IL-4Rα expression and brought back synergistic induction of arginase-1 in macrophages exposed also to IL-4. Taken together, increased expression of the IL-4Rα may represent the basis for the synergistic effect of IL-10 on IL-4-induced arginase-1 expression in macrophages.

Discussion

In the 13 years since the discovery of IL-10, major advances have been made in understanding the function of this important cytokine (1, 2). We now recognize that IL-10 plays an essential role in the endogenous anti-inflammatory response of the host. IL-10 acts primarily on activated macrophages, where IL-10R expression is highest. The IL-10R activates STAT3 and loss of this transcription factor in macrophages mimics loss of IL-10 itself (11), suggesting that most, if not all, IL-10 signal transduction proceeds through STAT3. Despite this knowledge, major gaps remain in understanding how IL-10 exerts its anti-inflammatory effects. For example, we do not know how STAT3 mediates the IL-10 signal, nor whether the effects of STAT3 are direct or via the synthesis of other proteins. We do not know how IL-10 regulates the large number of physiologically relevant targets that have been described and whether this is through a common mechanism or if diverse pathways are involved. Our study was designed to address two fundamental questions concerning IL-10 action. First, what spectrum of genes are induced by IL-10 with or without a concomitant inflammatory stimulus and second, what is the range of inflammatory genes regulated by IL-10?

Genes induced by IL-10

We found that IL-10 induced a highly restricted number of genes in resting macrophages. In LPS-activated macrophages, IL-10 induced a different set of genes. It is tempting to speculate that key anti-inflammatory genes may be represented in this latter group because the effects of IL-10 on macrophages are most clearly demonstrated with concomitant activation. Two independent signals from the IL-10R and a TLR may be necessary to engender the full range of anti-inflammatory mechanisms.

Several genes regulated by IL-10 with or without concomitant LPS stimulation warrant further investigation for their potential role in IL-10 signaling. One obvious candidate is SOCS3, a member of the SOCS family that inhibits cytokine receptor signaling by binding phosphotyrosine residues on key signaling molecules and targeting them for destruction via its ubiquitin E3 ligase activity (36). SOCS3 binds to gp130 (37, 38), the signaling component of IL-6 family cytokine receptors (39), but may have additional targets, as overexpression studies have shown that it can inhibit IFN-γ signaling (20). It has even been speculated that IL-10-induced SOCS3 might inhibit LPS-induced p38 MAPK signaling and thereby interfere with TNF-α mRNA translation (6). The question of whether SOCS3 indeed plays a role in the control of macrophage activation by IL-10 could best be answered using SOCS3-deficient macrophages. Because SOCS3-deficient embryos die in mid-gestation (40), we are in the process of generating radiation chimeras to perform such experiments in the near future. Other IL-10 targets also give potential clues to the anti-inflammatory effects of IL-10. Among these, three genes encoding proteins involved in MAPK and related pathways, GADD45α, GADD45γ, and Tpl-2, suggest that a focus of IL-10 signaling research should be on these pathways. The role of IL-10 in regulating MAPK and related pathways is presently a controversial topic and requires clarification at the molecular level (1, 6, 41).

Global effects of IL-10 on proinflammatory gene expression induced by LPS

We found that IL-10 regulates a large number of LPS-induced genes. Our study confirmed the inhibition by IL-10 of many previously reported proinflammatory gene products (Fig. 3⇑) and extended this finding at the genomic level with the identification of numerous new IL-10-repressed genes. Although IL-10 repressed the expression of a large fraction of LPS-induced genes, a further fraction (∼40%) remained unchanged. This result suggests two important interpretations that contribute to understanding the anti-inflammatory effects of IL-10. First, the large number of LPS-induced genes inhibited by IL-10 suggests a common mechanism is operative. It is unlikely that IL-10 induces a different mediator for each inflammatory target. We favor the interpretation that IL-10 regulates a limited group of gene products (transcriptionally and/or posttranscriptionally) that subsequently regulate the inflammatory targets. Second, it is unlikely that IL-10 targets more global cell processes such as transcriptional initiation, because of the large fraction of LPS-induced genes unaffected by the addition of IL-10. Therefore, the IL-10-induced anti-inflammatory mechanism is specific enough to target a fraction of LPS-induced genes while leaving others unaffected.

STAT3 is essential for all observed effects of IL-10

Previous work has suggested that STAT3 is crucial for IL-10 signaling (11, 42). This is most clearly shown in mice lacking STAT3 in macrophages and neutrophils which have a strikingly similar phenotype to IL-10-deficient mice (11). Other work using dominant-negative versions of STAT3 in macrophage cell lines suggested that IL-10 signals via STAT3-dependent and -independent pathways (43). Using STAT3-deficient macrophages, we show that all IL-10-induced genes tested require STAT3 and that inhibition of gene expression of proinflammatory targets also requires STAT3 signaling (Fig. 5⇑). Although we cannot rule out some STAT3-independent effects for IL-10, our results suggest that STAT3 is essential for most, if not all, IL-10 signaling.

IL-10 controls macrophage arginase expression in response to IL-4 and LPS

In addition to identifying candidate mediators of IL-10′s deactivating effects, we also expected to find genes affecting macrophage function in other ways. The up-regulation of IL-4Rα expression by IL-10 in a STAT3-dependent manner caught our attention, because it implied a possibly enhanced responsiveness to IL-4 as a functional consequence of exposure to IL-10. In fact, we observed that opposing changes in IL-4Rα expression induced by IL-10 or LPS in IL-10-deficient macrophages were linked to corresponding changes in the expression level of arginase-1 in response to IL-4 (Fig. 6⇑). These observations offer a mechanistic explanation for the previously described synergistic induction of arginase-1 expression by IL-4 and IL-10 (35). Further, the microarray experiments also showed that expression of the extrahepatic isoform arginase-2 in LPS-stimulated macrophages (33) is controlled by IL-10 (Table II⇑, Fig. 4⇑). Because the ability to make IL-10 also determines expression of arginase-1 in response to LPS (Fig. 6⇑) or the combination of TNF-α and IFN-γ (34), IL-10 increases total arginase levels in macrophages in multiple ways.

Concluding remarks

Certain caveats are evident in a microarray study of this nature. The most significant are the timepoints chosen for data analysis. In this study, the two timepoints chosen were based upon the well-recognized effects of IL-10 on proinflammatory mediator production. Thus, we focused on 45 min and 3 h as a representative window where the expression of TNF-α and several other cytokines and chemokines is substantially reduced in in vitro macrophage culture and in in vivo models where mice are challenged with TLR agonists. However, it is clear that IL-10 can have later effects that may be mediated by distinct mechanisms (41) and even have proinflammatory effects (44). A second caveat is that we can only observe changes in mRNA levels and IL-10 may induce a plethora of cellular changes at the proteome level that also contribute to its anti-inflammatory effects. Despite these limitations, our study has revealed several aspects of IL-10 function not previously appreciated. Understanding the rules that govern the IL-10-mediated shaping of the macrophage transcriptome and its subsequent influence on the proteome will provide insights into the endogenous anti-inflammatory response.

Acknowledgments

We thank Irmgard Förster for the gift of STAT3flox/− LysMcre mice, Andrew Pappas and Deepak Kaushal for help with software, and Martine Roussel for critical appraisal of the manuscript.

Footnotes

  • ↵1 This work was supported by American Heart Association Grant 0151039B to P.J.M., Cancer Center CORE Grant P30 CA 21765, and by the American Lebanese Syrian Association of Charities. R.L. was a recipient of a fellowship from the Deutsche Forschungsgemeinschaft (LA-1262/1).

  • ↵2 Current address: Boling Center, 711 Jefferson Avenue, No. 415, Memphis, TN 38163.

  • ↵3 Address correspondence and reprint requests to Dr. Peter J. Murray, Department of Infectious Diseases, St. Jude Children’s Research Hospital, 332 North Lauderdale, Memphis, TN 38105. E-mail address: peter.murray{at}stjude.org

  • 4 Abbreviations used in this paper: MAPK, mitogen-activated protein kinase; PDM, peritoneal-derived macrophages; BMDM, bone marrow-derived macrophages; IL-1ra, IL-1R antagonist; SOCS, suppressor of cytokine signaling; GADD, growth arrest and DNA damage; EST, expressed sequence tag; JE/MCP, JE/monocyte chemoattractant protein; Tpl, tumor progression locus; TLR, Toll-like receptor; C/EBP, CCAAT/enhancer binding protein; AMBP, α1-microglobulin/bikunin precursor.

  • Received April 8, 2002.
  • Accepted June 18, 2002.

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