To maintain homeostasis, macrophages must be capable of assuming either an inflammatory or an anti-inflammatory phenotype. To better understand the latter, we stimulated human macrophages in vitro with TLR ligands in the presence of high-density immune complexes (IC). This combination of stimuli resulted in a broad suppression of inflammatory mediators and an upregulation of molecules involved in tissue remodeling and angiogenesis. Transcriptomic analysis of TLR stimulation in the presence of IC predicted the downstream activation of AKT and the inhibition of GSK3. Consequently, we pretreated LPS-stimulated human macrophages with small molecule inhibitors of GSK3 to partially phenocopy the regulatory effects of stimulation in the presence of IC. The upregulation of DC-STAMP and matrix metalloproteases was observed on these cells and may represent potential biomarkers for this regulatory activation state. To demonstrate the presence of these anti-inflammatory, growth-promoting macrophages in a human infectious disease, biopsies from patients with leprosy (Hanseniasis) were analyzed. The lepromatous form of this disease is characterized by hypergammaglobulinemia and defective cell-mediated immunity. Lesions in lepromatous leprosy contained macrophages with a regulatory phenotype expressing higher levels of DC-STAMP and lower levels of IL-12, relative to macrophages in tuberculoid leprosy lesions. Therefore, we propose that increased signaling by FcγR cross-linking on TLR-stimulated macrophages can paradoxically promote the resolution of inflammation and initiate processes critical to tissue growth and repair. It can also contribute to infectious disease progression.

The phenotypic changes that macrophages undergo subsequent to their encounter with pathogen-associated molecular patterns have been well described (1). The cell surface receptors and downstream signaling molecules that activate transcription factors to drive inflammatory responses have been thoroughly studied. These so-called M1 (inflammatory) macrophages make important contributions to the initiation of immune responses, but their myriad inflammatory secretory products can cause tissue damage when left uncontrolled. Working in the murine system, our laboratory characterized a population of regulatory macrophages that were generated by TLR stimulation in the presence of a second “reprogramming” stimulus. Paradoxically, the increased signaling strength through the dual stimuli resulted in reduced inflammatory and increased anti-inflammatory cytokine production (27). We hypothesized that these cells may play a role in dampening inflammation during the resolution of immune responses.

The first reprogramming stimulus identified in the murine system was immune complexes (IC) that signal through the macrophage FcγR (6). In macrophages, IC induce the clustering of stimulatory FcγR, resulting in the phosphorylation of Syk (8, 9). This initiates a powerful signaling cascade, leading to actin remodeling, PI3K activation, and Ca+ mobilization (10). The most widely studied consequences of these signaling pathways in macrophages are the induction of phagocytosis and the generation of the respiratory burst, both important components of host defense. We previously demonstrated that FcγR ligation on TLR-stimulated murine macrophages can also result in the rapid and prolonged hyperphosphorylation of ERK, triggering chromatin remodeling at the IL-10 promoter, leading to increased IL-10 transcription (11).

A similar regulatory phenotype has not been described in human macrophages, and no biomarkers exist to identify these cells. Furthermore, our understanding of how to manipulate this activation state is limited. In this study, we use high-throughput approaches to characterize human regulatory macrophages generated in response to IC (R-Mϕ-IC) with the aim of identifying biomarkers that could be used for their identification in tissue. By providing a global picture of the behavior and function of these human macrophages, our studies revealed that IC can dampen inflammatory responses and inhibit the nuclear translocation of GSK3β to induce the transcription of genes promoting tissue growth, angiogenesis, and extracellular matrix reorganization.

To begin to examine whether these growth-promoting R-Mϕ-IC could be exploited by intracellular pathogens to promote uncontrolled intracellular growth, we examined macrophages from the skin of people with leprosy (Hanseniasis). Leprosy has been characterized as a “spectral” disease (12, 13). On the paucibacillary tuberculoid end of the spectrum, the pathogens are cleared by activated macrophages following the development of cell-mediated immunity (14, 15). Ab levels in this disease are typically low or absent (16). In contrast, humoral immunity predominates in lepromatous leprosy. Ab levels are high, and bacteria grow uncontrolled in dermal macrophages (12, 15). Cellular immunity appears to be defective because patients generally fail to mount a delayed-type hypersensitivity (DTH) response to skin test Ags (15). The uncontrolled intracellular growth of bacteria in macrophages associated with the presence of IC therefore define this permissive form of the disease.

Human monocyte-derived macrophages were purchased from HemaCare (Van Nuys, CA) or monocytes were differentiated in house using the Miltenyi Biotec Pan Monocyte Isolation Kit (San Diego, CA). Cells were cultured for 7–10 d in X-VIVO 15 serum-free media (Lonza, Walkersville, MD) containing 1% penicillin streptomycin, 1% l-glutamate (Life Technologies, Gaithersburg, MD), and 20 ng/ml recombinant human M-CSF (PeproTech, Rocky Hill, NJ). Prior to stimulation, M-CSF–containing medium was removed and replaced with X-VIVO 15 media containing 2.5% FBS (Atlanta Biologicals, Flowery Branch, GA). All studies on human monocyte-derived macrophages were approved by the University of Maryland and the MedImmune Institutional Review Boards.

Macrophage stimulation conditions were generated by adding 30 ng/ml Ultra-pure LPS from Escherichia coli K12 (InvivoGen, San Diego, CA) (LPS-Mϕ) or LPS in combination with soluble IC (R-Mϕ-IC), as described (7, 17). Particulate IC were generated by adding rabbit IgG to 1.1 μM latex spheres overnight. Macrophages were stimulated with TLR agonists, Pam3Csk4, polyinosinic-polycytidylic acid (Poly I:C), or heat-killed Listeria monocytogenes (HKLM) (InvivoGen) in the presence/absence of particulate IC. The AKT inhibitor (MK-2206 2HCl) and the GSK3 inhibitor (SB415286) were purchased from APExBIO Technology (Houston, TX) and Cayman Chemical (Ann Arbor, MI), respectively, and used at 20 μM. The GSK3β isoform-specific inhibitor (AZD2858) was provided by AstraZeneca and used at 750 nM.

Total RNA was extracted from cells, and poly(A)+-enriched cDNA libraries were generated using the Illumina TruSeq Sample Preparation Kit (San Diego, CA). Paired end reads (100 bp) were obtained using an Illumina HiSeq 1500. Trimmomatic was used to remove any remaining Illumina adapter sequences from reads and trim read ends with quality score <20 (18). Sequence quality metrics were assessed using FastQC (19). Reads were aligned to the human genome (hg19/GRCh37.62.v3) obtained from the University of California, Santa Cruz genome browser (20) (http://genome.ucsc.edu) using TopHat (v 2.0.13) (21), with parameters matching previous work (22). The abundance of reads mapped to coding features was determined using HTSeq (23). Quantile normalization and log2 transformation was applied to all samples (24). Limma was used to conduct differential expression analyses (25). The voom module was used to transform the databased on observational level weights derived from the mean-variance relationship prior to statistical modeling. Experimental batch effects were adjusted for by including experimental batch as a covariate in our statistical model. Differentially expressed genes were defined as genes with a log2 fold change (FC) >1 and Benjamini–Hochberg multiple-testing adjusted p value <0.05. All components of the statistical pipeline, named cbcbSEQ, can be accessed on GitHub (https://github.com/kokrah/cbcbSEQ/).

Cell culture supernatants were collected from macrophages at 24 h and analyzed using the SOMAscan proteomic assay (SOMAscan Assay 1.1k; SomaLogic, Boulder, CO). Relative fluorescence unit values from SOMAscan were normalized against hybridization control sequences to correct for any systematic effects introduced during hybridization. Median normalization was performed across samples within arrays. Group comparisons were performed using Bayesian modified linear model (Limma package in R) (26). Between groups, comparisons were assessed using contrast, and the p values of the moderated t test were Benjamini–Hochberg adjusted. Differentially expressed proteins were defined as FC ≥ 1.5 and false discovery rate ≤ 0.05.

RNAscope probes for IL-10, LIF, and matrix metalloproteases (MMP) 10 were custom designed by Advanced Cell Diagnostics (Newark, CA) with nucleotide accession numbers: https://www.ncbi.nlm.nih.gov/nuccore/NM_000572 (IL-10), https://www.ncbi.nlm.nih.gov/nuccore/NM_002421 (MMP1), and https://www.ncbi.nlm.nih.gov/nuccore/NM_002309 (LIF). Macrophages were stimulated in four-well chamber slides for 4 h. Slides were stained with RNAscope Multiplex Fluorescent Reagent Kit v2, mounted with Fluoromount-G with DAPI Thermo Fisher Scientific (Waltham, MA) and imaged using the Zeiss LSM 710 Confocal Laser Microscope (Carl Zeiss Microscopy, Jena, Germany). Fluorescence was quantified using Zen software by Zeiss.

Human monocytes were differentiated in ultra-low attachment plates. Allophycocyanin-conjugated Ab to dendritic cell–specific transmembrane protein (DC-STAMP) (mouse IgG2b, clone no. 788524) and BUV395-conjugated Ab to CD73 (mouse IgG1k, clone no. AD2) (BD Biosciences, Franklin Lakes, NJ) were applied to the surface of stimulated macrophages. Alexa Fluor 647–conjugated Ab to MMP10 (mouse IgG1, clone no. 110316) and PE-conjugated Ab to LIF (mouse IgG1k, clone no. 1F10) was applied to permeabilized macrophages following brefeldin treatment. Data acquisition was carried out in FACSCanto II (BD Biosciences); analyses were done on FlowJo version 10.

Human IL-10 and IL-12p40 were detected by sandwich ELISA kits purchased from eBioscience (San Diego, CA). ELISA kits for the remaining analytes were purchased from R&D Systems (Minneapolis, MN).

Ingenuity Pathway Analysis (IPA) software (27) was used to predict diseases, functions, and upstream regulators. Regulators with low numbers of known targets (<10) were removed. Pathway enrichment analysis was conducted using the Reactome Pathway Analysis package in R (28).

Phosphorylation of AKT signaling pathway molecules was assessed in whole cell lysates using PathScan AKT Signaling Ab Array Kit (Cell Signaling Technology, Danvers, MA). Bicinchoninic acid assay (Pierce Biotechnology, Waltham, MA) was used to determine protein concentration of the samples. Array densities were quantified using Image J software (29).

Nuclear and cytosolic fractions were isolated using NE-PER Nuclear Extraction Kit (Thermo Fisher Scientific). Protein lysates were incubated for 2 h at 4°C with protein agarose A (Santa Cruz Biotechnology, Dallas, TX). Phospho-ERK 1/2, phospho-AKT, cofilin, phospho-GSK3β, GSK3β, and histone H3 Abs were purchased from Cell Signaling Technology; phospho-GSK3α/β Ab was purchased from R&D Systems; and actin Ab was purchased from Santa Cruz Biotechnology. A conformation-specific anti-rabbit IgG (Cell Signaling Technology) was used as a secondary Ab when needed.

RNA for quantitative real-time PCR was isolated using the TRIzol method (Thermo Fisher Scientific). cDNA was synthesized using SuperScript Vilo cDNA Synthesis Kit (Thermo Fisher Scientific). Relative quantification of RNA was done using SYBR Green–based real-time PCR (Thermo Fisher Scientific). The samples were run in Roche Light Cycler 480. Relative differences were calculated using the ΔΔCt method with β-actin as a control.

Tissue fragments were cut on a microtome to 4–5-μm thick and stained with H&E and analyzed by light microscopy. The DC-STAMP immunohistochemical protocol was carried out using moist heat (95°C) for 20 min in citrate (pH 6) (Dako Target Retrieval Solution Cytomation). Endogenous peroxidase was blocked with hydrogen peroxide added to methanol (3%). Nonspecific reactions were blocked with powdered milk and diluted in PBS in a humid chamber for 30 min at room temperature. Sections were incubated with primary serum at 4°C. Biotinylated secondary Ab (DAKO kit LSAB 2 System Peroxidase K0675) was added as previously described (30). Streptavidin peroxidase complex (DAKO kit LSAB) was added for 30 min in a humid chamber at room temperature. Developing solution of diaminobenzidine (Sigma) plus a hydrogen peroxide solution was added for 5 min at room temperature. Washed slides were counterstained with Harris hematoxylin, washed, dehydrated, cleared, and mounted with Entellan.

RNA sequencing (RNA-seq) was performed to characterize global changes in gene expression in human macrophages under inflammatory or anti-inflammatory in vitro stimulation conditions (Supplemental Table I). The transcriptome of nonstimulated resting macrophages was compared with macrophages stimulated with LPS alone and macrophages stimulated with LPS in the presence of high-density IC (LPS + IC-Mϕ). For most of these studies, soluble IC formed by the addition of OVA/anti-OVA were used to costimulate macrophages. Principal component analysis of coding transcripts at 4 h poststimulation revealed samples from the same treatment groups clustering together (Supplemental Fig. 1A). Principal component 1 explained 75% of the variance, separating resting macrophages from those stimulated with LPS. Principal component 2 explained 13% of the variance and segregated LPS-Mϕ from LPS + IC-Mϕ (Supplemental Fig. 1A). We selected 4 h poststimulation for our analysis to identify early transcripts induced by LPS and those regulated directly by the addition of IC rather than those influenced by LPS-induced macrophage secretory products.

Stimulation of human macrophages with LPS resulted in numerous changes in gene expression, as previously reported (31, 32). Over 4500 genes were significantly differentially expressed in response to stimulation with LPS, with 2017 transcripts upregulated and 2521 downregulated, accounting for ∼38% of all detectable genes in the transcriptome (Supplemental Fig. 1B). The 10 most highly upregulated genes in LPS-treated macrophages, relative to nonstimulated cells, are shown in Fig. 1A. Consistent with previous reports (31, 33), LPS stimulation led to increased production of transcripts encoding inflammatory mediators, such as the chemokines CXCL9, CXCL10, CXCL11, and CCL8, the cytokines IL-6 and IL-12B, antimicrobial IRG1, and IDO1, an enzyme that converts tryptophan to kynurenine to limit tryptophan availability (34) (Fig. 1A, red bars). We previously demonstrated (4) that murine macrophages responded to stimulation in the presence of IC with decreased expression of IL-12 and increased expression of IL-10. In human macrophages, the addition of IC to LPS-stimulated cells resulted in a significantly lower expression of the inflammatory cytokines IL-6 and IL-12 and the inflammatory chemokines CXCL9, 10, 11, and CCL8 (Fig. 1A, blue bars). Overall, the addition of IC to LPS-stimulated human macrophages resulted in the differential expression of 1557 genes (13%, Supplemental Fig. 1B), including 925 transcripts that were significantly upregulated and 632 downregulated (Fig. 1B). Surprisingly, 80% of these differentially expressed human genes were not changed in similarly stimulated murine macrophages (Supplemental Fig. 1C).

FIGURE 1.

Global changes in gene expression following the stimulation of human macrophages in the presence of IC. Human monocyte-derived macrophages were stimulated with LPS (30 ng/ml) or LPS + IC (OVA/anti-OVA) for 4 h, and total mRNA was isolated and sequenced on the Illumina platform (n = 3). (A) The 10 most highly upregulated genes in LPS-stimulated macrophages are designated by red bars and expressed as FC relative to resting macrophages (mean ± SEM). Values for corresponding FC in LPS + IC–stimulated macrophages are designated by blue bars. Asterisks designate significant differences (adjusted p value ≤ 0.05) between LPS versus LPS + IC. (B) Volcano plot of genes expressed in LPS + IC relative to LPS alone. In parentheses are the number of genes upregulated or downregulated by >2-fold, with an adjusted p value ≤ 0.05. The box shows some of the most highly upregulated genes by FC and significance. Genes marked in red are associated with cell growth, angiogenesis, and extracellular matrix remodeling. (C) The top 10 most highly upregulated and downregulated genes in macrophages stimulated with LPS + IC relative to stimulation with LPS alone, expressed by log2 FC (mean ± SEM). (D) RT-PCR of IL-10 transcripts following stimulation with TLR agonists, Pam3Csk4, Poly I:C, or HKLM in the absence (black bars) or presence (blue bars) of particulate IC composed of latex beads coated with rabbit polyclonal IgG. The y-axis represents expression relative to Actin/Rab7 (mean ± SEM, n = 3). *p ≤ 0.05.

FIGURE 1.

Global changes in gene expression following the stimulation of human macrophages in the presence of IC. Human monocyte-derived macrophages were stimulated with LPS (30 ng/ml) or LPS + IC (OVA/anti-OVA) for 4 h, and total mRNA was isolated and sequenced on the Illumina platform (n = 3). (A) The 10 most highly upregulated genes in LPS-stimulated macrophages are designated by red bars and expressed as FC relative to resting macrophages (mean ± SEM). Values for corresponding FC in LPS + IC–stimulated macrophages are designated by blue bars. Asterisks designate significant differences (adjusted p value ≤ 0.05) between LPS versus LPS + IC. (B) Volcano plot of genes expressed in LPS + IC relative to LPS alone. In parentheses are the number of genes upregulated or downregulated by >2-fold, with an adjusted p value ≤ 0.05. The box shows some of the most highly upregulated genes by FC and significance. Genes marked in red are associated with cell growth, angiogenesis, and extracellular matrix remodeling. (C) The top 10 most highly upregulated and downregulated genes in macrophages stimulated with LPS + IC relative to stimulation with LPS alone, expressed by log2 FC (mean ± SEM). (D) RT-PCR of IL-10 transcripts following stimulation with TLR agonists, Pam3Csk4, Poly I:C, or HKLM in the absence (black bars) or presence (blue bars) of particulate IC composed of latex beads coated with rabbit polyclonal IgG. The y-axis represents expression relative to Actin/Rab7 (mean ± SEM, n = 3). *p ≤ 0.05.

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The most highly upregulated transcripts in LPS + IC-Mϕ relative to LPS-Mϕ included genes that have been associated with cell growth, angiogenesis, and remodeling of the extracellular matrix (Fig. 1B, 1C). The 10 most highly upregulated genes included several matrix metalloproteinases (MMP1, MMP3, and MMP10) known to be involved in tissue remodeling, angiogenesis, and extracellular cytokine regulation (35, 36). Some of the other top upregulated genes included TM4SF1 [cell growth and angiogenesis (37)], LIF [self-renewal of stem cells (38)], DC-STAMP (39), OCSTAMP [phagocytic activity and immune tolerance (40)], ANGPTL4 [lipid metabolism (41)], AREG [cell growth, EGF, and TGFA signaling (42)], IL-1RL2 [IL-36 signaling and epithelial barrier function (43)], and GREM1 [monocyte chemotaxis inhibition (44)]. Of the 30 most highly upregulated genes (by FC and p value), 12 genes have been reported by others to be directly involved in cell growth and angiogenesis (Fig. 1B, red). The 10 most highly downregulated genes in LPS + IC-Mϕ included IL-12B (TH1 responses), CCL8 (inflammatory chemokine), and CH25H (lipid metabolism and chemotaxis) (Fig. 1C), consistent with our premise that human macrophages stimulated with LPS + IC exhibit immunoregulatory activity.

To determine whether the reprogramming of macrophages to an anti-inflammatory phenotype is restricted to a single TLR, human macrophages were stimulated with other TLR ligands, including Pam3CysK, Poly I:C, and HKLM. The restriction of reprogramming to soluble IC was also tested by using particulate IC, consisting of IgG adsorbed to beads (Supplemental Fig. 1D). Stimulation of macrophages with other TLRs plus particulate IC resulted in an increase in the production of IL-10 (Fig. 1D) as well as other regulatory transcripts including MMP1, MMP10, and ANGL4 (Supplemental Fig. 1D).

To characterize the secretome of R-Mϕ, we performed a SOMAscan analysis on cell culture supernatants of human macrophages collected 24 h following stimulation. FCs in secreted protein levels were compared with the corresponding gene expression data from RNA-seq using Spearman correlation to determine whether changes in secreted proteins corroborate the transcriptional changes observed in RNA-seq (Supplemental Fig. 2A). The r value of 0.65 (p value = 0.0001) indicates a positive correlation between RNA and protein changes. To show that IC were, indeed, binding to macrophages FcγR, we measured FcγR1 (CD64) and FcγR3 (CD16) expression before and after stimulation. As expected, the addition of IC to macrophages resulted in FcγR internalization and reduced surface expression of these two receptors (Supplemental Fig. 2B).

Compared with LPS stimulation, LPS + IC–stimulated macrophages increased the secretion of 78 proteins and decreased the secretion of 149 proteins (FC > 1.5 and false discovery rate < 0.05) (Fig. 2A). The 17 most highly upregulated secretory products in R-Mϕ-IC relative to LPS-Mϕ are shown in Fig. 2B expressed as FC relative to nonstimulated macrophages. These secretory products include several MMPs (MMP3, MMP10, MMP12), IL-10, Activin A (INHBA), and CCL20. An ELISA was performed to confirm that stimulation of human macrophages with LPS in the presence of IC induced a significant increase in the secretion of selected proteins compared with LPS alone (Fig. 2C, blue bars). Quantitative real-time PCR at 4 h poststimulation demonstrated a similar upregulation of 10 of the 17 genes at the transcript level (Fig. 2D).

FIGURE 2.

The macrophage secretome. Cell culture supernatants collected from human monocyte-derived macrophages at 24 h following stimulation with LPS or LPS + IC were compared with that of unstimulated macrophages. (A) Differential protein expression, as measured by SOMAScan technology, in the supernatants of LPS or LPS + IC–stimulated macrophages relative to unstimulated macrophages are represented by a heatmap. (B) The top 17 upregulated proteins in LPS + IC relative to LPS alone and their FC in LPS + IC– (blue) or LPS-stimulated macrophages (red). (C) Supernatants were analyzed by ELISA to measure the accumulation of seven proteins that were identified in the SOMAscan analysis following no stimulation (black) or stimulation with LPS + IC (blue) or LPS alone (red) (mean ± SEM, n = 5) (D) RT-PCR was used to measure transcript levels of 10 of the genes that were identified in the SOMAscan analysis (4 h poststimualtion). Bars represent log2 FC (mean ± SEM, n = 6 versus nonstimulated macrophages). (E) The top 14 downregulated proteins from the SOMAscan analysis when comparing LPS + IC to LPS stimulation are shown. Dots represent LPS + IC (blue) or LPS alone (red) log2 FC relative to unstimulated macrophages. (F) Supernatants of stimulated macrophages were analyzed by ELISA to measure the downregulation of IL-6, IL-12(p40), and CCL8 following stimulation with LPS + IC (blue) or LPS (red) (mean ± SEM, n = 3). Statistical significance indicated in (C), (D), and (F) was calculated using a paired t test. Asterisks designate significant differences (*p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001) between LPS versus LPS + IC.

FIGURE 2.

The macrophage secretome. Cell culture supernatants collected from human monocyte-derived macrophages at 24 h following stimulation with LPS or LPS + IC were compared with that of unstimulated macrophages. (A) Differential protein expression, as measured by SOMAScan technology, in the supernatants of LPS or LPS + IC–stimulated macrophages relative to unstimulated macrophages are represented by a heatmap. (B) The top 17 upregulated proteins in LPS + IC relative to LPS alone and their FC in LPS + IC– (blue) or LPS-stimulated macrophages (red). (C) Supernatants were analyzed by ELISA to measure the accumulation of seven proteins that were identified in the SOMAscan analysis following no stimulation (black) or stimulation with LPS + IC (blue) or LPS alone (red) (mean ± SEM, n = 5) (D) RT-PCR was used to measure transcript levels of 10 of the genes that were identified in the SOMAscan analysis (4 h poststimualtion). Bars represent log2 FC (mean ± SEM, n = 6 versus nonstimulated macrophages). (E) The top 14 downregulated proteins from the SOMAscan analysis when comparing LPS + IC to LPS stimulation are shown. Dots represent LPS + IC (blue) or LPS alone (red) log2 FC relative to unstimulated macrophages. (F) Supernatants of stimulated macrophages were analyzed by ELISA to measure the downregulation of IL-6, IL-12(p40), and CCL8 following stimulation with LPS + IC (blue) or LPS (red) (mean ± SEM, n = 3). Statistical significance indicated in (C), (D), and (F) was calculated using a paired t test. Asterisks designate significant differences (*p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001) between LPS versus LPS + IC.

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The addition of IC to LPS-stimulated macrophages also resulted in the downregulation of several secreted products (Fig. 2E). The secretion of proinflammatory chemokines (4547) CXCL11, CXCL13, CCL8, and CCL15 was decreased by the addition of IC to LPS-stimulated macrophages as was the secretion of the cytokine IL-6. Protease inhibitors and complement pathway proteins were also inhibited, indicating that IC costimulation downregulates several pathways of inflammation. An ELISA confirmed the decrease in the secretion of IL-6, IL-12 (which is not included in the SOMAscan platform), and CCL8 by the addition of IC to LPS-stimulated macrophages (Fig. 2F).

To determine the functional significance of the differentially expressed genes in R-Mϕ, the RNA-seq differential expression data were uploaded into the IPA tool. The Diseases and Functions report from IPA predicted increased activation of angiogenesis, cell proliferation, and tumor vulnerability (Fig. 3A) and a decreased activation of inflammation and rheumatic diseases (Fig. 3B). In total, 1337 unique genes contributed to the predicted upregulated functions and 716 unique genes contributed to the 33 predicted downregulated functions. The IPA Diseases and Functions report is consistent with a prosurvival, progrowth, and anti-inflammatory phenotype of macrophages following stimulation in the presence of IC.

FIGURE 3.

Functional properties of macrophages stimulated in the presence of IC. Differentially expressed genes (DEGs) in macrophages (FC ≥ 2 or ≤ −2) stimulated with LPS + IC were compared with cells stimulated with LPS alone and uploaded into the IPA Program, and the Diseases and Functions Report was generated (n = 3). Bar graphs (left) represent the top 20 (A) positively and (B) negatively enriched pathways ranked by z-score. Enriched diseases and functions were manually categorized into broader groups (pie charts) in a nonoverlapping manner.

FIGURE 3.

Functional properties of macrophages stimulated in the presence of IC. Differentially expressed genes (DEGs) in macrophages (FC ≥ 2 or ≤ −2) stimulated with LPS + IC were compared with cells stimulated with LPS alone and uploaded into the IPA Program, and the Diseases and Functions Report was generated (n = 3). Bar graphs (left) represent the top 20 (A) positively and (B) negatively enriched pathways ranked by z-score. Enriched diseases and functions were manually categorized into broader groups (pie charts) in a nonoverlapping manner.

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Taken together, our data confirm the work of several groups (31, 32), which is that TLR stimulation alone triggers major gene expression changes in human macrophages, leading to an inflammatory macrophage phenotype (so-called M1). The addition of soluble or particulate IC at the time of stimulation leads to a downregulation of inflammatory gene expression and an enhanced array of immunoregulatory genes that have important roles in cell growth and repair, tissue remodeling, and angiogenesis.

The identification of signaling pathways and key regulators of transcriptional programs has the potential to lead to new treatments that induce or inhibit the regulatory macrophage phenotype in vivo. To identify the pathways and master regulators involved in generation of the R-Mϕ-IC phenotype, differentially upregulated genes from RNA-seq (R-Mϕ-IC versus LPS-Mϕ) were analyzed using the Reactome pathway analysis package in R. The results showed enrichment of transcripts associated with IL-10 production as well as the MAP kinases and members of the AKT signaling pathway (Fig. 4A). Previous publications in the murine system implicated a role for AKT/ERK signaling in macrophage stimulation (11, 48, 49), so we proceeded to analyze phosphorylation of proteins in the AKT/ERK pathway. Although AKT and ERK are part of distinct pathways, they share upstream regulators, and their pathways interact at multiple points. An Ab array for phosphorylated proteins in the AKT/ERK pathway was used, adding protein lysates from human macrophages 20 min after stimulation (Fig. 4B). LPS alone modestly activated the phosphorylation of AKT and ERK (Fig. 4C), whereas LPS + IC amplified phosphorylation of each of these proteins (Fig. 4C, gray bars). AMPK was used as a control whose phosphorylation was not increased in response to IC (Fig. 4C). Several other kinases, including mTOR, PTEN, and PDK1 were similarly unresponsive to IC (Supplemental Fig. 2C). Western blotting confirmed that phosphorylation of ERK (Supplemental Fig. 2D) and AKT at threonine 473 was higher under LPS + IC–treated conditions (Fig. 4D, 4E).

FIGURE 4.

Signaling in R-Mϕ-IC. (A) A bar graph of 10 enriched (ordered by adjusted p value < 0.02) Reactome pathways among genes upregulated in macrophages stimulated with LPS + IC versus LPS (n = 3). The size of the bar along the x-axis indicates the number of differentially upregulated genes found in each pathway. (B) Representative image of Ab array (Cell Signaling Technology) from whole cell lysates of nonstimulated human macrophages or those stimulated for 20 min with LPS alone or LPS + IC. (C) Densitometry was calculated using Image J software. Values are mean FC compared with nonstimulated macrophages, and error bars are SEM (n = 3). (D) A representative Western blot of macrophage lysates confirms Ab array results for p-AKT thr473 and total AKT. (E) Densitometry of three independent Western blots to quantify AKT phosphorylation following stimulation with LPS or LPS + IC relative to nonstimulated cells (mean ± SEM, n = 3). Statistical significance was calculated using a paired t test; *p ≤ 0.05.

FIGURE 4.

Signaling in R-Mϕ-IC. (A) A bar graph of 10 enriched (ordered by adjusted p value < 0.02) Reactome pathways among genes upregulated in macrophages stimulated with LPS + IC versus LPS (n = 3). The size of the bar along the x-axis indicates the number of differentially upregulated genes found in each pathway. (B) Representative image of Ab array (Cell Signaling Technology) from whole cell lysates of nonstimulated human macrophages or those stimulated for 20 min with LPS alone or LPS + IC. (C) Densitometry was calculated using Image J software. Values are mean FC compared with nonstimulated macrophages, and error bars are SEM (n = 3). (D) A representative Western blot of macrophage lysates confirms Ab array results for p-AKT thr473 and total AKT. (E) Densitometry of three independent Western blots to quantify AKT phosphorylation following stimulation with LPS or LPS + IC relative to nonstimulated cells (mean ± SEM, n = 3). Statistical significance was calculated using a paired t test; *p ≤ 0.05.

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Previous studies have demonstrated that activated AKT can inhibit GSK3 signaling (49) and furthermore that GSK3 inhibition can increase IL-10 expression in macrophages (50). This led us to hypothesize that activation of AKT by IC may permit the expression of regulatory molecules by inhibiting GSK3. It is known that GSK3β shuttles between the cytoplasm and the nucleus, and active GSK3β has been shown to accumulate in the nucleus (51), so we probed GSK3β in cytoplasmic and nuclear fractions of R-Mϕ-IC lysates. Western blotting revealed that LPS stimulation led to an increase of GSK3β in the nucleus (Fig. 5A). However, costimulation with IC prevented nuclear translocation, significantly reducing nuclear levels of GSK3β compared with LPS alone (Fig. 5A, 5B). An ATP-competitive inhibitor of GSK3α/β (52) was used in lieu of IC to determine if GSK3 inhibition of LPS-stimulated macrophages could upregulate some of the transcripts that were induced in R-Mϕ-IC. When combined with LPS stimulation, the GSK3 inhibitor SB415286 transcriptionally upregulated 7 out of the 10 genes tested in the panel of markers for LPS + IC (Fig. 5C). GSK3 inhibition did not reduce the expression of three inflammatory cytokines typically decreased by costimulation with IC (Fig. 5D). These results indicate that GSK3 inhibition is important for inducing the expression of regulatory genes in human macrophages but does not play a role in inhibiting LPS-triggered inflammatory responses.

FIGURE 5.

GSK3β inhibition in R-Mϕ-IC. (A) Western blotting for GSK3β in the nuclear (left) or cytosolic (right) fractions of macrophage lysates collected 30 min after stimulation with LPS alone, LPS and IC (L + IC), or LPS in combination with SB415286 (20 μM), an inhibitor of GSK3 (L + GI). (B) Densitometry was calculated using Image J software. Bars represent mean FC ± SEM in the nucleus over cytosolic levels (n = 3). (C) RT-PCR results for macrophages stimulated with LPS (black), LPS + IC (gray), or LPS in the presence of 20 μM SB415286 to inhibit GSK3 (stippled). RNA was collected 7 h after stimulation and expressed as FC (log10) ± SEM relative to nonstimulated macrophages (n = 4, *p ≤ 0.05; **p ˂ 0.01). (D) The production of inflammatory cytokines IL-12(p40), IL-6, and TNF was measured by ELISA 7 h after stimulation with LPS alone (black) or LPS + SB415286 (gray) to inhibit GSK3 (mean ± SEM n = 3). (E) Macrophages were stimulated with LPS alone (black bars) or LPS with AZD2858 (750 nM), a small molecule inhibitor specific for GSK3β (gray bars). The levels of IL-10, MMP1, and MMP10 in supernatants was measured by ELISA 16 h later. Statistical significance for (B) through (E) was calculated using a paired t test. mean ± SEM, n = 3, *p ≤ 0.05).

FIGURE 5.

GSK3β inhibition in R-Mϕ-IC. (A) Western blotting for GSK3β in the nuclear (left) or cytosolic (right) fractions of macrophage lysates collected 30 min after stimulation with LPS alone, LPS and IC (L + IC), or LPS in combination with SB415286 (20 μM), an inhibitor of GSK3 (L + GI). (B) Densitometry was calculated using Image J software. Bars represent mean FC ± SEM in the nucleus over cytosolic levels (n = 3). (C) RT-PCR results for macrophages stimulated with LPS (black), LPS + IC (gray), or LPS in the presence of 20 μM SB415286 to inhibit GSK3 (stippled). RNA was collected 7 h after stimulation and expressed as FC (log10) ± SEM relative to nonstimulated macrophages (n = 4, *p ≤ 0.05; **p ˂ 0.01). (D) The production of inflammatory cytokines IL-12(p40), IL-6, and TNF was measured by ELISA 7 h after stimulation with LPS alone (black) or LPS + SB415286 (gray) to inhibit GSK3 (mean ± SEM n = 3). (E) Macrophages were stimulated with LPS alone (black bars) or LPS with AZD2858 (750 nM), a small molecule inhibitor specific for GSK3β (gray bars). The levels of IL-10, MMP1, and MMP10 in supernatants was measured by ELISA 16 h later. Statistical significance for (B) through (E) was calculated using a paired t test. mean ± SEM, n = 3, *p ≤ 0.05).

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To determine if a GSK3β isoform-specific inhibitor could also induce an anti-inflammatory response and if the response could be observed at the protein level, the small molecule inhibitor of the GSKβ, AZ2848, was used in combination with LPS to activate macrophages. ELISA analysis showed that GSK3β-specific inhibition significantly upregulated IL-10. MMP1 and 10 secretion trended toward upregulation but did not reach statistical significance because of the high variability in donor responses (Fig. 5E).

Just as macrophages assume a continuum of phenotypes (2), so do the biomarkers. This makes the definitive identification of biomarkers for specific human macrophage phenotypes a difficult task. The transient nature of the inflammatory and regulatory phenotypic changes adds to the challenge. Therefore, two parallel approaches were taken to identify potential biomarkers for human R-Mϕ-IC (1): in situ hybridization to visualize transcript expression and (2) flow cytometry and immunohistochemistry to identify protein expression.

Three genes, IL-10, LIF, and MMP10, were chosen from the RNA-seq analysis as potential RNA biomarkers based on their high FC when comparing R-Mϕ-IC to LPS-Mϕ and nonstimulated Mϕ (see Fig. 1B). Macrophages from three donors were fixed and stained using custom probes developed by Advanced Cell Diagnostics. RNAscope confirmed our RNA-seq analysis, showing little to no expression of these three transcripts (Fig. 6A, 6D) in resting nonstimulated macrophages. LPS-stimulated macrophages showed a slight increase in the expression of transcripts for IL-10 but little to no increase in transcripts for LIF and MMP10 (Fig. 6B, 6D). Conversely, macrophages stimulated with LPS + IC (Fig. 6C) showed a significant increase in mean fluorescent intensity per cell of all three transcripts (Fig. 6D). Therefore, a combination of probes for multiple regulatory transcripts may prove to be a useful technique for the identification of human R-Mϕ-IC.

FIGURE 6.

Biomarker identification on R-Mϕ-IC. RNAscope, a modified fluorescence in situ hybridization technique developed by Advanced Cell Diagnostics, was used to identify R-Mϕ transcriptional markers. Probes for LIF (green), MMP10 (red), and IL-10 (pink) were added to (A) resting nonstimulated macrophages or those stimulated with (B) LPS or (C) LPS + IC. Representative RNAscope images are shown in (A)–(C), and the mean intensity per cell ± SEM (n = 3) was quantified (D) using Zen Software and expressed as FC relative to nonstimulated (NS) (*p ≤ 0.05). (E) Monolayers of human macrophages were stimulated with LPS (left) or LPS+ particulate IC (right) and stained with mAb to CD73 followed by HRP-conjugated anti-mouse IgG. (F) Flow cytometry of macrophages stimulated for 16 h with LPS in the presence or absence of soluble IC (OVA–anti-OVA). DC-STAMP expression on nonstimulated (NS), LPS-stimulated (LPS), and LPS + IC–stimulated (LIC) was analyzed. The mean fluorescence intensity and percentage of positive cells are shown (error bars represent SEM, **p ≤ 0.01). (G) Macrophages were stimulated in brefeldin prior to permeabilization, fixation, and staining with MMP10 or LIF. The gray peak represents unstimulated cells, the lightly colored peaks represent LPS stimulation, and the darker profiles represent LPS + IC stimulation.

FIGURE 6.

Biomarker identification on R-Mϕ-IC. RNAscope, a modified fluorescence in situ hybridization technique developed by Advanced Cell Diagnostics, was used to identify R-Mϕ transcriptional markers. Probes for LIF (green), MMP10 (red), and IL-10 (pink) were added to (A) resting nonstimulated macrophages or those stimulated with (B) LPS or (C) LPS + IC. Representative RNAscope images are shown in (A)–(C), and the mean intensity per cell ± SEM (n = 3) was quantified (D) using Zen Software and expressed as FC relative to nonstimulated (NS) (*p ≤ 0.05). (E) Monolayers of human macrophages were stimulated with LPS (left) or LPS+ particulate IC (right) and stained with mAb to CD73 followed by HRP-conjugated anti-mouse IgG. (F) Flow cytometry of macrophages stimulated for 16 h with LPS in the presence or absence of soluble IC (OVA–anti-OVA). DC-STAMP expression on nonstimulated (NS), LPS-stimulated (LPS), and LPS + IC–stimulated (LIC) was analyzed. The mean fluorescence intensity and percentage of positive cells are shown (error bars represent SEM, **p ≤ 0.01). (G) Macrophages were stimulated in brefeldin prior to permeabilization, fixation, and staining with MMP10 or LIF. The gray peak represents unstimulated cells, the lightly colored peaks represent LPS stimulation, and the darker profiles represent LPS + IC stimulation.

Close modal

Immunohistochemistry and flow cytometry were also used to identify biomarkers on R-Mϕ-IC. The upregulation of CD73 on regulatory macrophages was visualized by immunohistochemistry on macrophages stimulated in vitro with LPS plus particulate IC (Fig. 6E). Using flow cytometry, we observed an increase in DC-STAMP mean fluorescent intensity as well as the number of DC-STAMP+ macrophages after stimulation with LPS plus soluble IC, relative to both LPS-Mϕ and nonstimulated Mϕ (Fig. 6F). The production of both MMP10 and LIF was increased slightly following LPS stimulation and further increased by stimulation with LPS + IC (Fig. 6G). These data indicate that no one biomarker can reliably identify R-Mϕ-IC but rather suggest that a combination of surface and cytosolic Ags may be used to identify these macrophages in tissue.

Leprosy (Hanseniasis) can present in different clinical forms (16). The lepromatous form of the disease is associated with high IgG levels, a defective skin DTH response to lepromin Ag (15, 16), and bacterial persistence in dermal macrophages. The defect in macrophage clearance of the bacteria and the presence of high IgG levels in lesions suggested a macrophage phenotype similar to the in vitro stimulated R-Mϕ-IC described above. We therefore examined the phenotype macrophages in lepromatous and tuberculoid leprosy lesions by immunohistochemistry. In the lepromatous form of the disease, we observed high levels of DC-STAMP on macrophages (Fig. 7, top, right) coupled with low levels of IL-12 (Fig. 7, bottom right). These cells also expressed a pan macrophage marker, CD68, and MMP10 (Supplemental Fig. 3A, 3B). In contrast, macrophages from the tuberculoid form of leprosy (Fig. 7, left) expressed lower levels of DC-STAMP and higher levels of IL-12 (Fig. 7A), consistent with an inflammatory M1 macrophage. DC-STAMP expression was quantitated by measuring peroxidase intensity, confirming that tuberculoid lesions expressed less DC-STAMP than lepromatous lesions (Supplemental Fig. 3C). Thus, human tissue macrophages in the IgG-rich environment of lepromatous leprosy fail to restrict the intracellular growth of bacteria and exhibit markers consistent with a regulatory phenotype.

FIGURE 7.

Immunohistochemistry of macrophages in human skin from patients with Hanseniasis. (A and B) Tuberculoid Hanseniasis in (A) a panoramic view showing in the reticular dermis (Rd). Two granulomas are designated with asterisks and in (B) high magnification showing intense cellular DC-STAMP labeling (positive macrophages in dark-brown cytoplasmic staining). (C and D) Lepromatous Hanseniases in (C) a panoramic view showing two granulomas in the reticular dermis (Rd) and two granulomas designated by asterisks. In (D), note higher DC-STAMP positive cells (positive immunolabeled macrophages in dark-brown cytoplasmic staining). Note numerous inflammatory vacuolated macrophages (white arrows). (E) Tuberculoid Hanseniasis. In the reticular dermis (Rd), one granuloma is designated by an asterisk with intense cellular IL-12 labeling (positive macrophages in dark-brown cytoplasmic staining). (F) Lepromatous Hanseniases. Note no granuloma formation and the presence of a diffuse exudate of inflammatory vacuolated macrophages (black arrows). Scale bars, (A and C) 64 μm and (B and D–F) 16 μm. Immunohistochemical of the streptavidin peroxidase method counter stained with Harris hematoxylin. Ep, epithelium; Pd, papilar dermis; Rd, reticular dermis.

FIGURE 7.

Immunohistochemistry of macrophages in human skin from patients with Hanseniasis. (A and B) Tuberculoid Hanseniasis in (A) a panoramic view showing in the reticular dermis (Rd). Two granulomas are designated with asterisks and in (B) high magnification showing intense cellular DC-STAMP labeling (positive macrophages in dark-brown cytoplasmic staining). (C and D) Lepromatous Hanseniases in (C) a panoramic view showing two granulomas in the reticular dermis (Rd) and two granulomas designated by asterisks. In (D), note higher DC-STAMP positive cells (positive immunolabeled macrophages in dark-brown cytoplasmic staining). Note numerous inflammatory vacuolated macrophages (white arrows). (E) Tuberculoid Hanseniasis. In the reticular dermis (Rd), one granuloma is designated by an asterisk with intense cellular IL-12 labeling (positive macrophages in dark-brown cytoplasmic staining). (F) Lepromatous Hanseniases. Note no granuloma formation and the presence of a diffuse exudate of inflammatory vacuolated macrophages (black arrows). Scale bars, (A and C) 64 μm and (B and D–F) 16 μm. Immunohistochemical of the streptavidin peroxidase method counter stained with Harris hematoxylin. Ep, epithelium; Pd, papilar dermis; Rd, reticular dermis.

Close modal

To our knowledge, this work provides the first characterization of human macrophages stimulated in the presence of IC. A combination of bioinformatic and functional analyses indicate that FcγR cross-linking in concert with TLR stimulation results in a population of macrophages with anti-inflammatory and growth-promoting activity. We have begun to identify biomarkers on these regulatory macrophages (R-Mϕ-IC) because of the potential therapeutic value of targeting these cells to enhance/prolong immune responses or conversely to induce these cells to mitigate autoimmunity.

We confirm the work of many groups (31, 32), showing that TLR ligation on macrophages results in a generalized inflammatory response and the early transcription of inflammatory chemokines and cytokines. IDO1, an enzyme that limits tryptophan availability to intracellular pathogens (34), is also one of the most highly upregulated transcripts following TLR ligation of human macrophages. The addition of a second stimulus to activate FcγR not only fails to amplify the inflammatory signature but actively reverses it, resulting in a significant decrease in 632 transcripts, including all seven of the above-mentioned inflammatory mediators (Fig. 1A). By IPA analysis, the genes most significantly reduced are generally involved in inflammation, rheumatic diseases, and cell death (Fig. 3). This costimulation also resulted in the upregulation of 925 transcripts (Fig. 1B), including many proteins involved in cell growth and differentiation, neovascularization, and tumor growth (Fig. 3). Twelve of the top 30 transcripts induced by the addition of IC (Fig. 1B) have been reported to be associated with cell growth and differentiation, including AREG (42), LIF (38), DC-STAMP (39), INHBA (53), and OCSTAMP (54). The top 30 upregulated transcripts also included three MMPs (MMP1, MMP3, and MMP10) and five cytokine-like molecules (IL-10, LIF, CSF2, IL-36RN, and TSLP).

We performed a SOMAscan analysis to detect secreted proteins from stimulated human macrophages, and the results were largely consistent with the RNA-seq (Supplemental Fig. 2A). The addition of IC broadly suppressed several LPS-induced cytokines and chemokines while inducing the secretion of soluble mediators involved in the regulation of inflammation. In this study, we present a panel of secreted proteins that may be appropriate for ELISA markers of this phenotype, with IL-10, MMP1, and activin A (INHBA) among the most abundant secretory products. The upregulated transcription and secretion of several matrix metalloproteinases by R-Mϕ-IC suggests that regulatory macrophages contribute to cell motility, angiogenesis, and tissue remodeling. These gene products cannot only degrade ECM components but also regulate extracellular signaling molecules (36). MMPs can cleave growth factors to release their active forms (55), suppress immune responses following infection (56, 57), and inactivate inflammatory chemokines and mediators (58, 59). Not surprisingly, MMP1, MMP3, and MMP10 are associated with tumor metastasis and angiogenesis (60). Given these actions, we propose that although regulatory macrophages contribute to the resolution of immune responses and the tissue repair, they could also have deleterious effects on host responses to infections and cancer.

Identifying the signaling pathways that lead to the phenotypic changes in macrophages may provide targets to manipulate immune/inflammatory responses. Our bioinformatics analysis predicted that genes associated with AKT/PI3K signaling pathway were involved in R-Mϕ-IC transcriptomic changes. The AKT pathway is a complex signaling cascade that can regulate metabolism based on nutrient availability (61). Because AKT activation lies upstream of so many pathways, it became important to determine which AKT substrate was responsible for the gene changes observed in the regulatory phenotype induced by IC. GSK3 is a signaling kinase that is constitutively active in the cell, only becoming inactivated through phosphorylation of its substrate binding site (62). Recently, GSK3 was found to have anti-inflammatory activity when a small molecule inhibitor of GSK3 increased survival in mice with endotoxemia (63, 64). We demonstrated that stimulation of macrophages with LPS and GSK3 inhibitor partially mimicked the LPS + IC phenotype, upregulating genes involved in growth and repair without influencing the production of inflammatory cytokines. Additionally, GSK3β is a transcription factor known to interact with AP-1, CREB, and NF-κB, among others (65), and is also involved in the regulation of chromatin remodeling (66). GSK3β has been found to have an inhibitory effect on AP-1 and CREB, both of which are involved in IL-10 transcriptional control (50, 64). We found reduced levels of GSK3β in the nucleus after LPS + IC stimulation and demonstrated that GSK3β inhibition not only augments IL-10 production but also amplifies the transcription of matrix metalloproteinases and growth-promoting factors in macrophages. These findings may explain previous observations that GSK3β inhibition is involved in wound healing and angiogenesis (67, 68).

We used RNAscope technology to visualize transcripts within fixed macrophages following stimulation. IC-induced regulatory macrophages could be identified through their increased expression of transcripts for IL-10, LIF, and MMP10. If used in combination with a macrophage marker such as CD68, we propose that this method can be used for the identification of regulatory macrophages in tissue. The identification of protein biomarkers for macrophage activation states represents a challenge because of the dynamic and transient nature of macrophage activation. Despite this, we used flow cytometry to demonstrate that regulatory macrophages upregulate several biologically important proteins, including MMPs and DC-STAMP. DC-STAMP is a cell surface protein that, despite its name, is also expressed on stimulated macrophages. This protein is mostly known for its role in the regulation of osteoclast differentiation (69) but is also implicated in cancer cell survival (70). Although usually discussed in the context of dendritic cells, DC-STAMP has been associated with increased phagocytosis and reduced Ag presentation and cytokine production (71, 72). DC-STAMP has been shown to be regulated by ERK (73), which may explain why its expression is increased following FcγR ligation.

To determine whether R-Mϕ-IC exist in human tissue, we turned to an infectious disease in which bacteria grow uncontrolled in dermal macrophages. Lepromatous leprosy (Hanseniasis) has long been associated with hyperglobulinemia and defective DTH responses. In the present work, we examined biomarkers on lesion macrophages that fail to provide host defense. Because we observe an increase in DC-STAMP on macrophages that are failing to provide adequate host defense, it is tempting to speculate that the regulatory macrophage phenotype could be driving this permissiveness. This idea is consistent with the high levels of IgG known to be present in the lepromatous form of the disease. Further studies in Hanseniasis are needed to determine how macrophage phenotype can influence disease progression.

In summary, our studies reveal the generation of macrophages with an anti-inflammatory, prohealing phenotype that arise following stimulation in the presence of FcγR cross-linking. These regulatory macrophages may provide intracellular pathogens a safe haven for intracellular growth. These observations can likely be applied to a variety of infectious, inflammatory, or neoplastic diseases in which the identification of these macrophages may help explain disease pathology.

This work was supported in part by National Institutes of Health National Institute of Allergy and Infectious Diseases Grant NIH R01 GM 102589.

The online version of this article contains supplemental material.

Abbreviations used in this article:

DC-STAMP

dendritic cell–specific transmembrane protein

DTH

delayed-type hypersensitivity

FC

fold change

HKLM

heat-killed Listeria monocytogenes

IC

immune complex

IPA

Ingenuity Pathway Analysis

LPS + IC

LPS in the presence of high-density IC

LPS + IC-Mϕ

macrophages stimulated with LPS in the presence of high-density IC

MMP

matrix metalloprotease

Poly I:C

polyinosinic-polycytidylic acid

RNA-seq

RNA sequencing.

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The authors have no financial conflicts of interest.

Supplementary data