Lipopolysaccharide-Elicited TSLPR Expression Enriches a Functionally Discrete Subset of Human CD14+ CD1c+ Monocytes

Francesco Borriello, Raffaella Iannone, Sarah Di Somma, Viviana Vastolo, Giuseppe Petrosino, Feliciano Visconte, Maddalena Raia, Giulia Scalia, Stefania Loffredo, Gilda Varricchi, Maria Rosaria Galdiero, Francescopaolo Granata, Luigi Del Vecchio, Giuseppe Portella and Gianni Marone
J Immunol May 1, 2017, 198 (9) 3426-3435; DOI: https://doi.org/10.4049/jimmunol.1601497

Abstract

Thymic stromal lymphopoietin (TSLP) is a cytokine produced mainly by epithelial cells in response to inflammatory or microbial stimuli and binds to the TSLP receptor (TSLPR) complex, a heterodimer composed of TSLPR and IL-7 receptor α (CD127). TSLP activates multiple immune cell subsets expressing the TSLPR complex and plays a role in several models of disease. Although human monocytes express TSLPR and CD127 mRNAs in response to the TLR4 agonist LPS, their responsiveness to TSLP is poorly defined. We demonstrate that TSLP enhances human CD14+ monocyte CCL17 production in response to LPS and IL-4. Surprisingly, only a subset of CD14+ CD16− monocytes, TSLPR+ monocytes (TSLPR+ mono), expresses TSLPR complex upon LPS stimulation in an NF-κB– and p38-dependent manner. Phenotypic, functional, and transcriptomic analysis revealed specific features of TSLPR+ mono, including higher CCL17 and IL-10 production and increased expression of genes with important immune functions (i.e., GAS6, ALOX15B, FCGR2B, LAIR1). Strikingly, TSLPR+ mono express higher levels of the dendritic cell marker CD1c. This evidence led us to identify a subset of peripheral blood CD14+ CD1c+ cells that expresses the highest levels of TSLPR upon LPS stimulation. The translational relevance of these findings is highlighted by the higher expression of TSLPR and CD127 mRNAs in monocytes isolated from patients with Gram-negative sepsis compared with healthy control subjects. Our results emphasize a phenotypic and functional heterogeneity in an apparently homogeneous population of human CD14+ CD16− monocytes and prompt further ontogenetic and functional analysis of CD14+ CD1c+ and LPS-activated CD14+ CD1c+ TSLPR+ mono.

Introduction

Thymic stromal lymphopoietin (TSLP) is a cytokine produced mainly by epithelial cells in response to inflammatory or microbial stimuli (1). TSLP binds to the TSLP receptor (TSLPR) complex, a heterodimer composed of TSLPR and IL-7 receptor α (IL-7R-α or CD127), and activates several signaling pathways, including JAK-STAT5 (2). TSLPR complex is expressed by epithelial cells and also several immune cell subsets, including dendritic cells (DCs). Importantly, several lines of evidence support a model in which TSLP activation of DCs results in Th2 differentiation in vitro and type 2 immunity in vivo (3, 4). As such, TSLP has been involved in the development of atopic diseases, tissue remodeling, and the modulation of the immune response to ectoparasite infections and cancers (1, 5). Nevertheless, the breadth of TSLP activity is not limited to type 2 immunity-related conditions. For example, TSLP is expressed in psoriatic lesions and instructs CD40L-activated DCs to produce IL-12 and IL-23, which play a central role in psoriasis pathogenesis (6, 7). This cytokine has also been implicated in the pathogenesis on rheumatic diseases, at least in part by activating DCs (8). Finally, TSLP dampens myeloid cell inflammatory response in an experimental model of sepsis (9). Thus, understanding the response of myeloid cells (i.e., DCs, macrophages, neutrophils, and monocytes) to TSLP may be relevant for several physiologic and pathologic conditions. Although human monocytes stimulated with LPS (the major component of the outer membrane of Gram-negative bacteria) express TSLPR and CD127 mRNAs (10), their responsiveness to TSLP is poorly defined.

Activation of DCs with TSLP induces several phenotypic and functional responses, including the production of the chemokine CCL17/thymus and activation-regulated chemokine that promotes the recruitment of CCR4-expressing cells (e.g., Th2 and T regulatory lymphocytes) (1). Monocytes and macrophages activated with IL-4 or IL-13 also produce CCL17 in a STAT6-dependent manner (11, 12). Interestingly, TSLP and IL-4 or IL-13 synergize to induce CCL17 production by mouse macrophages (13). We have recently shown that the STAT5-activating cytokines IL-3 and GM-CSF synergize with IL-4 to enhance CCL17 production by human monocytes and macrophages (14). Because TSLP activates STAT5, we reasoned that also TSLP could enhance CCL17 production by human monocytes activated with LPS and IL-4. By investigating human monocyte responsiveness to TSLP, we unexpectedly found that only a subset of human CD14+ monocytes express the TSLPR complex upon LPS stimulation, and we proceeded to characterize this subset. We demonstrate that TSLPR+ monocytes (TSLPR+ mono) express distinct phenotypic, functional, and transcriptomic profiles compared with TSLPR− monocytes (TSLPR− mono), and are also enriched for a subset of CD14+ CD1c+ monocytes. The translational relevance of these findings is highlighted by the higher expression of TSLPR and CD127 mRNAs in monocytes isolated from patients with Gram-negative sepsis compared with healthy control subjects.

Materials and Methods

Cell isolation and culture

The study protocol involving the use of human blood cells was approved by the Ethics Committee of the University of Naples Federico II. Cells were isolated from buffy coats of healthy donors. Blood was layered onto Histopaque-1077 (Sigma-Aldrich), and mononuclear cells were collected at the interface. Monocytes were further purified with CD14 Microbeads (Miltenyi Biotec). Purity of cell preparations was >95% as assessed by flow cytometry (CD14+ cells). Cells were cultured in cIMDM-5 (IMDM, 5% FCS, 1× nonessential amino acids, 1× UltraGlutamine, 25 mM HEPES, 5 μg/ml gentamicin [Lonza]) in 96-well flat-bottom plates (105 monocytes per well) in a final volume of 250 μl. For experiments involving flow cytometry or FACS, cells were cultured in suspension (1.5-ml tubes for flow cytometry, 50-ml tubes for FACS) at a concentration not >2 × 106 cells/ml, then spun down and collected for the subsequent staining protocols. For experiments aimed at evaluating the modulation of TSLPR complex expression, cells were cultured in cIMDM-0.5 (0.5% FCS).

Cells were treated with different combinations of LPS (Escherichia coli O26:B6) 10, 100, and 1000 ng/ml; PHA 10 μg/ml (Sigma); IL-4 10 ng/ml; TSLP 5 ng/ml (Miltenyi Biotec); anti-human TNF-α 1 μg/ml; mouse IgG1 κ isotype control 1 μg/ml (eBioscience); P3CSK4 10, 100, and 1000 ng/ml; Poly(I:C) 1 μg/ml; flagellin 10 ng/ml; imiquimod 1 μg/ml; ODN2006 1 μM; heat-killed Gram-negative bacteria Pseudomonas aeruginosa, heat-killed Gram-positive bacterium Staphylococcus aureus, and heat-killed Gram-negative bacteria E. coli O111:B4 (monocytes/bacteria ratio 1:10) (InvivoGen); BAY11-7082 0.5, 1, and 2 μM; SP600125 2 μM; CHIR-98014 200 nM; wortmannin 1 μM (Selleckchem); UO126 2 μM; LY294002 10 μM; and SB203580 2 μM (Cell Signaling Technology).

ELISA

Cytokine concentrations were measured in cell-free supernatants using commercially available ELISA kits for CCL17 (R&D Systems), TNF-α, IL-1β, IL-6, and IL-10 (eBioscience). Standard curves were generated with a Four Parametric Logistic curve fit, and data were analyzed using MyAssays Analysis Software Solutions (MyAssays: http://www.myassays.com).

Flow and imaging cytometry

Flow and imaging cytometry experiments were performed with purified monocytes. For surface staining, cells were stained (20 min at 4°C) in PBS + 10% human AB serum (Lonza) + 0.05% NaN3 (staining buffer). For phosphoprotein staining, cells were rested in cIMDM-0.5 for 1 h and stimulated with the indicated cytokines for 15 min. Then cells were fixed with paraformaldehyde (EM-grade; final concentration 1.5%; Electron Microscopy Sciences) and permeabilized with absolute ice-cold methanol. Cells were stained (30 min at room temperature) in staining buffer. The following Abs were used: anti-human phospho-STAT5 Alexa Fluor 647 (clone 47, dilution 1:20), anti-human TSLPR allophycocyanin (clone 1A6, dilution 1:40) (BD Biosciences), anti-human CD127 PE-Vio770 (clone MB15-18C9, dilution 1:20), anti-human CD14 FITC (clone TÜK4, dilution 1:20), anti-human CD16 PE (clone VEP13, dilution 1:20), anti-human CD11b PE (clone M1/70.15.11.5, dilution 1:20), anti-human CD11c PE (clone REA618, dilution 1:20), anti-human HLA-DR PE (clone REA332, dilution 1:20), and anti-human CD1c PE (clone AD5-8E7, dilution 1:20) (Miltenyi Biotec). For flow cytometry experiments, samples were acquired on MACSQuant Analyzer 10 (Miltenyi Biotec) and analyzed using FlowJo v10. Doublets, debris (identified based on forward and side scatter properties), and dead cells (identified with Zombie Violet Fixable Viability Kit; BioLegend) were excluded from the analysis. Data are expressed as percentage of positive cells and median fluorescence intensity (MFI). For imaging cytometry experiments, samples were acquired on Amnis ImageStreamx Mark II (EMD Millipore). Unfocused cells and doublets were excluded from the analysis, and representative images were taken in the following gates: TSLPR+ CD127+ and TSLPR− CD127+ cells.

FACS

For sorting of CD14hi CD16− and CD14+ CD16+ cells, monocytes were left untreated and stained with anti-CD14 and anti-CD16 Abs. For sorting of TSLPR+ cells, monocytes were cultured for 14 h as indicated earlier and then stained with anti-TSLPR. Stainings were performed in PBS + 10% human AB serum (Lonza) for 30 min at 4°C; then cells were washed with PBS + 0.2% BSA, filtered (preseparation filters [70 μm]; Miltenyi Biotec), and sorted through a BD FACSAria III (BD Biosciences). Purity of sorted cells was >90%. The following Abs were used to stain 20–30 × 106 monocytes: anti-human TSLPR allophycocyanin (clone 1A6, dilution 1:20; BD Biosciences), anti-human CD14 FITC (clone TÜK4, dilution 1:7), and anti-human CD16 PE (clone VEP13, dilution 1:8) (Miltenyi Biotec).

Mixed leukocyte reaction

FACS-sorted TSLPR+ mono and TSLPR− mono were stimulated for 14 h with LPS or LPS + IL-4 in cIMDM-5. Then cells were washed and cultured in cIMDM-5 for 7 d with CD4+ T lymphocytes isolated with CD4 Microbeads (Miltenyi Biotec) from unrelated donors and labeled with CFSE (5 μM; Thermo Fisher). Unstimulated and PHA-stimulated CD4+ T lymphocytes labeled with CFSE were used as controls. On day 7, nonadherent cells (i.e., CD4+ T lymphocytes) were harvested, acquired on an MACSQuant Analyzer 10 (Miltenyi Biotec), and analyzed using FlowJo v10. Doublets, debris (identified based on forward and side scatter properties), and dead cells (identified with Zombie Violet Fixable Viability Kit [BioLegend]) were excluded from the analysis. Unstimulated CFSE-labeled CD4+ T lymphocytes were used to set the gate for CFSElow lymphocytes (i.e., proliferating lymphocytes).

Time-lapse microscopy

TSLPR+ mono and TSLPR− mono were stimulated for 14 h with LPS or LPS + IL-4 in cIMDM-5. Over this time window digital phase-contrast images of 15 fields per well were taken every 15 min with the Operetta High-Content Imaging System (PerkinElmer). To quantify cell movements, we calculated square displacement for each cell as the sum of squared displacement of the x- and y-axes. Then the average of square displacements was calculated to compute the mean square displacement (MSD) for each condition.

RNA isolation and real-time RT-PCR

Total RNA was extracted using TRIzol reagent (Invitrogen), according to the manufacturer’s protocol. For RNA sequencing (RNA-seq), RNA was extracted using the ReliaPrep RNA Cell Miniprep System (Promega). Reverse transcription of 500 ng of total RNA was performed using SuperScript III Reverse Transcriptase (Invitrogen, Carlsberg, CA), following the manufacturer’s instructions. Real-time RT-PCR was performed in duplicate by using Universal SYBR Green Supermix (Bio-Rad) on CFX96 Real Time detection system (Bio-Rad). Relative quantification of gene expression was calculated by the Δ cycle threshold (Ct) (relative expression × 104) method. Each Ct value was normalized to the respective ubiquitin C (UBC) Ct value. The following primer pairs were used: TSLPR forward 5′-GGTGACGTGTTCTGACCTGT-3′; TSLPR reverse 5′-TTCCTGTTTGGACTGCCACT-3′; CCL17 forward 5′-TCCAGGGATGCCATCGTTTTT-3′; CCL17 reverse 5′-TCCCTCACTGTGGCTCTTCT-3′; GAS6 forward 5′-CTCTCTCTGTGGCACTGGTAG-3′; GAS6 reverse 5′-TATGCTCCACGGCCAGGA-3′; ALOX15B forward 5′-CTGAGCAAGGAGCCTGGAGA-3′; ALOX15B reverse 5′-GCTCATCCGGATAGGTGCC-3′; FCGR2B forward 5′-ACTGAGAGTGACTGGGCTGA-t-3′; FCGR2B reverse 5′-CACAGCTGTCCACAGAAGCA-3′; LAIR1 forward 5′-CCGTCGGACAACAGTCACAA-3′; LAIR1 reverse 5′-AAGACCACTGAGACCCCGAT-3′; MYC forward 5′-ATTCTCTGCTCTCCTCGACG-3′; MYC reverse 5′-AGCCTGCCTCTTTTCCACA-3′; KLF4 forward 5′-AGGGAGAAGACACTGCGTCA-3′; KLF4 reverse 5′-TCCCGCCAGCGGTTATTC-3′; PPARG forward 5′-AAAGGCGAGGGCGATCTTG-3′; PPARG reverse 5′-GATGGCCACCTCTTTGCTCT-3′; UBC forward 5′-GGTCGCAGTTCTTGTTTG-3′; UBC reverse 5′-GATGGTCTTACCAGTCAGA-3′.

RNA-seq and bioinformatic analysis

The following samples were used for next generation sequencing experiments: three pairs of TSLPR− and TSLPR+ mono, each pair obtained from a single donor. Next generation sequencing experiments, comprising samples quality control, were performed by Genomix4life S.R.L. (Baronissi, Salerno, Italy). Indexed libraries were prepared from 1 μg each of purified RNA with TruSeq Stranded mRNA Sample Prep Kit (Illumina) according to the manufacturer’s instructions. Libraries were quantified using the Agilent 2100 Bioanalyzer (Agilent Technologies) and pooled such that each index-tagged sample was present in equimolar amounts, with final concentration of the pooled samples of 2 nM. The pooled samples were subject to cluster generation and sequencing using an Illumina HiSEquation 2500 System (Illumina) in a 2 × 100 paired-end format at a final concentration of 8 pmol. The raw sequence files generated (.fastq files) underwent quality-control analysis using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/, release 0.10.1). Raw reads were filtered and trimmed based on quality and adapter inclusion using Trimmomatic (release 0.35) (15).

The human genome and gene annotation file (h38.83) were downloaded from EnsEMBL. First, the genome was indexed using STAR (release 2.5.0b) (16). Then, filtered and trimmed reads were aligned on the genome. SAM output files from STAR were converted into BAM, then sorted and indexed using the view, sort, index, and programs from the SAMtools software collection (release 0.1.19-96b5f2294a) (17).

The gene annotation file has been collapsed into a synthetic file using the createSyntheticTranscripts function from the easyRNASeq package (release 2.6.1) (18). This procedure has been performed to avoid counting reads multiple times by collapsing all existing transcripts of a single gene locus into a synthetic transcript containing every exon of that gene. The featureCounts program was used to count the number of reads overlapping genes (release 1.5.0-p1) (19). All the genes not showing at least one reads mapping per million mapped reads (cpm) in at least two samples were discarded. The bioconductor edgeR package (release 3.12.0) (20) was used to calculate the differential expression of genes between two conditions. This package measures the significance of the variation in expression levels using the dispersion of the expression levels among sample replicates. According to the comparison, significantly upregulated/downregulated genes were sorted based on the p value. The top 500 differentially expressed genes (p ≤ 0.05) were used to perform Gene Ontology (GO) enrichment analysis using DAVID tool (release 6.7) (21). Their expression levels were represented in the heatmap using MeV software (multiexperiment viewer, v4.8.1) (22).

Accession numbers

The accession number for the RNA-seq data reported in this paper is ArrayExpress: E-MTAB-4996 (European Nucleotide Archive: http://www.ebi.ac.uk/ena).

Statistical analysis

Statistical analysis was performed with Prism 6 (GraphPad Software). The p values were calculated with two-tailed paired t test, repeated measures one- or two-way ANOVA corrected for multiple comparisons, or Wilcoxon matched-pairs signed rank test as indicated in figure legends. A p value <0.05 was considered significant.

Results

TSLP enhances human monocyte production of CCL17

We have recently shown that the STAT5-activating cytokines IL-3 and GM-CSF synergize with the STAT6-activating cytokine IL-4 to enhance human monocyte production of CCL17 (14). Because TSLP also activates STAT5 (2), we stimulated monocytes with TSLP and IL-4 for 21–24 h in the absence or presence of LPS, which induces monocyte expression of TSLPR and CD127 mRNAs (10), and assessed the production of CCL17. In the absence of LPS, only low levels of CCL17 could be detected. CCL17 production could not be detected when monocytes were stimulated with TSLP in the presence or absence of LPS (which is consistent with the absence of myeloid DCs in our monocyte preparations). Interestingly, the addition of TSLP to LPS and IL-4 significantly enhanced CCL17 production (Fig. 1A). Comparable results were obtained when monocytes were primed with LPS for 14 h and then stimulated for 21–24 h with IL-4 and TSLP in the presence or absence of LPS (Supplemental Fig. 1A). To better characterize the effects of TSLP on monocyte activation, we evaluated the production of TNF-α, IL-1β, IL-6, and IL-10 upon stimulation with IL-4 and TSLP in the presence of LPS. However, none of these cytokines was significantly modulated by TSLP (Fig. 1B). Thus, human monocyte activation with TSLP specifically enhances IL-4–induced CCL17 production in the presence of LPS.

FIGURE 1.
FIGURE 1.

TSLP enhances LPS- and IL-4–induced CCL17 production. (A and B) Human CD14+ monocytes were stimulated with IL-4 and TSLP in the absence or presence of LPS for 21–24 h. CCL17, TNF-α, IL-1β, IL-6, and IL-10 levels were assessed by ELISA in cell-free supernatants. Data are shown as mean + SEM of 11 (A) or 8 (B) independent experiments. *p < 0.05, determined by repeated measures one-way ANOVA with Tukey post hoc test.

TLR4 activation elicits a subset of human TSLPR+ mono that preferentially originates from CD16− monocytes

Because TSLP is able to modulate monocyte production of CCL17, we then looked for the surface expression of TSLPR complex subunits (TSLPR and CD127) by flow cytometry. Freshly isolated monocytes did not express TSLPR and CD127, nor did they phosphorylate STAT5 in response to TSLP (data not shown). Critically, stimulation of monocytes for 14 h with LPS induced the expression of TSLPR complex subunits on a small percentage of monocytes (TSLPR+ mono), whereas the vast majority expressed only CD127 without TSLPR, or neither of them (TSLPR− mono) (Fig. 2A). We confirmed by imaging cytometry that TSLPR and CD127 colocalize on the surface of TSLPR+ mono (Fig. 2C). Accordingly, when monocytes were pretreated with LPS and then stimulated with TSLP for 15 min, a comparable percentage of monocytes phosphorylated STAT5 (p-STAT5+ cells) (Fig. 2B), indicating that LPS pretreatment induced the expression of a functional TSLPR complex only on a small subset of monocytes.

FIGURE 2.
FIGURE 2.

LPS stimulation elicits a subset of TSLPR+ mono. (A, B, D, and E) Human CD14+ monocytes were stimulated with LPS (A and B), several TLR agonists (D), or heat-killed bacteria (E) for 14 h, and the percentages of TSLPR+ CD127+ cells (TSLPR+ mono) (A, D, and E) or p-STAT5+ cells in response to TSLP (B and D) were assessed by flow cytometry. A representative contour plot of TSLPR and CD127 expression is shown in (A) (left panel). (C) Cells were treated as in (A), and the expression and colocalization of TSLPR and CD127 were assessed in TSLPR+ mono (upper panel) or TSLPR− mono (lower panel) by imaging cytometry. A representative cell for each subset is shown. Data are shown as mean + SEM of nine (A and B), four (D), or six (E) independent experiments. *p < 0.05, **p < 0.01, determined by two-tailed paired t test (A and B) and repeated measures one-way ANOVA with Dunnett post hoc test (D and E).

Next, we sought to characterize whether TLR agonists other than LPS (which is a TLR4 agonist) elicit TSLPR+ mono. To this aim, we pretreated monocytes with LPS (TLR4 agonist), P3CSK4 (TLR2 agonist), Poly(I:C) (TLR3 agonist), flagellin (TLR5 agonist), imiquimod (TLR7 agonist), or ODN 2006 (TLR9 agonist); then we assessed the expression of TSLPR and CD127 or p-STAT5 in response to TSLP. TLR4 activation induced the highest percentage of TSLPR+ mono (Fig. 2D), although higher concentrations of the TLR2 agonist P3CSK4 also induced TSLPR+ mono (Supplemental Fig. 1B). Interestingly, TSLPR+ mono were also elicited by heat-killed Gram-negative bacteria (P. aeruginosa and E. coli O111:B4), whereas the heat-killed Gram-positive bacterium S. aureus had a negligible effect on TSLPR and CD127 surface expression (Fig. 2E).

Human monocytes can be divided into classical, intermediate, and nonclassical monocytes based on their expression of CD14 and CD16 (CD14hi CD16−, CD14+ CD16+, and CD14dim CD16+, respectively) (23), although other markers have been proposed to distinguish these subsets (24). The majority of monocytes in our preparations (which were isolated based on CD14 expression) had a CD14hi CD16− phenotype (classical monocytes), whereas only a small percentage had a CD14+ CD16+ phenotype (intermediate monocytes) and virtually no CD14dim CD16+ (nonclassical) monocytes (Supplemental Fig. 1C, upper panel). To assess the ontogeny of TSLPR+ mono, we FACS-sorted CD14hi CD16− and CD14+ CD16+ monocytes, and stimulated them with LPS before assessing TSLPR surface expression. Only a small percentage of CD14+ CD16+ monocytes became TSLPR+ (Supplemental Fig. 1C, lower panel). Because most of the monocytes in our preparations were CD16−, it is likely that TSLPR+ mono preferentially originated from this subset with a rather minor contribution of CD14+ CD16+ monocytes.

TLR4-activated signaling pathways required for the induction of TSLPR+ mono

Proinflammatory and infectious stimuli induce the expression of TSLPR complex, as well as its ligand TSLP, in epithelial cells (25–27). However, the expression of TSLPR complex in this model is not mediated by NF-κB, because overexpression of the NF-κB subunits p50 and p65 does not induce the TSLPR complex, nor does the inhibitor BAY 11-7082 (which inhibits TNF-α–induced IκBα phosphorylation and thus NF-κB nuclear translocation) impair its expression. On the contrary, both approaches affect TSLP expression (25). To evaluate the contribution of NF-κB to the expression of TSLPR complex in our model, we stimulated monocytes with LPS in the presence of different concentrations of BAY 11-7082. Interestingly, BAY 11-7082 concentration-dependently reduced the percentage of TSLPR+ mono (Fig. 3A). Because TNF-α induces TSLPR complex expression in epithelial cells and human hematopoietic progenitors (25, 28), we also evaluated the contribution of LPS-induced autocrine TNF-α to TSLPR expression. The addition of an anti–TNF-α blocking Ab to LPS did not significantly modify the percentage of TSLPR+ mono (Supplemental Fig. 2A), thus ruling out any role for TNF-α in our model. TLR4 also signals through MAPKs (i.e., ERK1/2, p38, JNK) (29), which may be involved in the modulation of the TSLPR complex. Indeed, the p38 inhibitor SB203580 reduced (Fig. 3B), whereas inhibitors of MEK1/2 (U0126, which in turn inhibits ERK1/2) and JNK (SP600125) had no effect on the percentage of TSLPR+ mono (Supplemental Fig. 2B).

FIGURE 3.
FIGURE 3.

Signaling pathways required for TSLPR+ mono emergence. (A–C) Human CD14+ monocytes were stimulated with LPS in the presence or absence of BAY 11-7082 (NF-κB inhibitor) (A), SB203580 (p38 inhibitor) (B), and wortmannin, LY294002 (PI3K inhibitors), and CHIR-98014 (GSK-3 inhibitor) (C) for 14 h, and the percentages of TSLPR+ CD127+ cells (left panels) or p-STAT5+ cells in response to TSLP (right panels) were assessed by flow cytometry. Data are shown as mean + SEM of five (A) or six (B and C) independent experiments. *p < 0.05, **p < 0.01, determined by repeated measure one-way ANOVA with Tukey post hoc test.

LPS-mediated TLR4 activation triggers the PI3K/Akt pathway, which exerts anti-inflammatory properties at least in part by restraining NF-κB and GSK-3 proinflammatory activities (29). Because the TLR4-mediated monocyte proinflammatory activation is required for eliciting TSLPR+ mono, we evaluated the role of PI3K in our model. The PI3K inhibitors wortmannin and LY294002 markedly increased the percentage of TSLPR+ mono. To test the balance between PI3K and GSK-3, we used the GSK-3 inhibitor CHIR-99021. Interestingly, CHIR-99021 alone did not modulate the percentage of TSLPR+ mono. However, when CHIR-99021 was administered along with the PI3K inhibitors it completely reverted their effect, because the percentage of TSLPR+ mono in these conditions was comparable with that of monocytes stimulated with LPS without any inhibitors (Fig. 3C).

TSLPR+ mono exhibit discrete phenotypic and functional features

The results obtained so far support a model in which the balance between intracellular proinflammatory (e.g., NF-κB, p38, GSK-3) and anti-inflammatory (e.g., PI3K) pathways activated by LPS dictates the emergence of TSLPR+ mono. We next decided to characterize the phenotypic and functional features of TSLPR+ and TSLPR− mono. First, we evaluated the surface expression of the myeloid cell markers CD14, CD11b, and CD11c. Although they were expressed by both subsets, TSLPR+ mono exhibited higher levels of CD11c and lower levels of CD14 and CD11b (Supplemental Fig. 2C). Then, we assessed the response of TSLPR+ and TSLPR− mono to LPS, IL-4, and TSLP. Monocytes were pretreated for 14 h with LPS, FACS-sorted into TSLPR+ and TSLPR− mono, and stimulated for 16–18 h in the presence of LPS without or with IL-4, TSLP, or a combination of them. Interestingly, TSLPR mRNA was expressed by TSLPR+ mono, whereas it was not induced in TSLPR− mono under any of the tested conditions (Fig. 4A), suggesting that once the distinction between these subsets is established during LPS pretreatment, it remains stable. We also assessed CCL17 mRNA levels, and surprisingly we found that only TSLPR+ mono expressed CCL17 in response to IL-4 (Fig. 4B), despite both subsets phosphorylating STAT6 in response to IL-4 (data not shown), and TSLPR+ mono did not express higher levels of transcription factors involved in monocyte/macrophage alternative activation (i.e., MYC, KLF4, PPARG) (Supplemental Fig. 2D) (30–33). These results were confirmed by evaluating CCL17 protein levels in cell-free supernatants (Fig. 4C). To account for possible cross-talks between TSLPR+ mono and TSLPR− mono that could result in the expression of CCL17 also in the TSLPR− subset, we pretreated monocytes with LPS and IL-4, and FACS-sorted TSLPR+ and TSLPR− mono were directly harvested for RNA isolation without further restimulation. In keeping with our previous results, the expression of TSLPR and CCL17 mRNAs was higher in the TSLPR+ subset (Fig. 4D). To further characterize the response of TSLPR+ and TSLPR− mono, we evaluated the production of TNF-α, IL-1β, IL-6, and IL-10 and found that in each of the tested conditions, TSLPR+ mono produced, respectively, lower and higher levels of IL-6 and IL-10. TSLPR+ mono showed reduced TNF-α production only when stimulated with LPS and TSLP, whereas no significant differences in the production of IL-1β were observed (Fig. 4E).

FIGURE 4.
FIGURE 4.

TSLPR+ mono display a different cytokine profile. (A–E) Human CD14+ monocytes were pretreated with LPS (A–C and E) or LPS + IL-4 (D) for 14 h and FACS-sorted into TSLPR− and TSLPR+ mono. Then cells were directly harvested for RNA isolation and real-time RT-PCR analysis (D) or further stimulated with LPS, IL-4, and TSLP for 16–18 h (A–C and E). Cytokine levels were assessed in cell-free supernatants by ELISA (C and E), and cells were harvested for RNA isolation and real-time RT-PCR analysis (A and B). Black bars represent TSLPR− mono; white bars represent TSLPR+ mono. Data are shown as mean + SEM of four (A–C and E) or two (D) independent experiments. *p < 0.05, **p < 0.01, determined by repeated measures one-way ANOVA with Sidak post hoc test (A–C, and E).

These results support the concept of an LPS-induced functional specialization in an apparently homogeneous population of human CD14+ monocytes. To gain further insights into this model, we performed a transcriptomic analysis of FACS-sorted TSLPR+ and TSLPR− mono restimulated with LPS for 14 h. GO analysis revealed distinct enrichment for biological processes between TSLPR− and TSLPR+ mono (Fig. 5A, 5B). Moreover, these cell subsets also exhibited different gene expression profiles (Fig. 5C). Unexpectedly, TSLPR+ mono expressed higher levels of CD1C, a marker of DCs (34, 35) assigned to the conventional DC 2 (cDC2) lineage (36), and also of genes that are commonly associated with Ag processing and presentation (e.g., LAMP3, MHC class II genes) (Supplemental Tables I, II). These results are consistent with the increased surface expression of HLA-DR (Fig. 6A). We also confirmed the surface expression of CD1c in TSLPR+ mono, whereas it was not expressed by TSLPR− mono (Fig. 6B). Because one of the main features of DCs is Ag presentation and the ability to induce T cell proliferation, we challenged TSLPR+ and TSLPR− mono (restimulated for 14 h with LPS or LPS and IL-4) with CFSE-labeled CD4+ T lymphocytes isolated from an unrelated donor. TSLPR+ mono restimulated with LPS were the most efficient in promoting T cell proliferation, although the overall proliferation rate was low and consistent with the monocytic origin of these cells (Fig. 6C). GO analysis also revealed enrichment for genes associated with cell motility in TSLPR+ mono (Fig. 5B). To corroborate these findings, we performed time-lapse microscopy of TSLPR+ and TSLPR− mono restimulated as indicated earlier. TSLPR+ mono displayed increased cell motility (Supplemental Videos 1–4) and MSD (Fig. 6D) in cell-tracking experiments. Finally, we confirmed that TSLPR+ mono restimulated with LPS or LPS and IL-4 expressed higher levels of genes with important immune functions (Fig. 6E): GAS6, ligand of the TAM receptor AXL that exerts several functions including promoting tumor growth (37); ALOX15B, an enzyme involved in the synthesis of proresolving lipid mediators (38); FCGR2B and LAIR1, inhibitory receptors that bind, respectively, the C region of IgG and collagen or collagen-like motif-containing proteins (e.g., C1q and surfactant protein D) (39, 40).

FIGURE 5.
FIGURE 5.

Transcriptomic analysis of TSLPR− and TSLPR+ mono restimulated with LPS. (A and B) Pie charts show the top 10 biological functions by the 178 (A) and 322 (B) genes upregulated in TSLPR− and TSLPR+ human monocytes, respectively. The color gradient indicates the GO terms ordered based on the p value (p ≤ 0.01, darker colors indicate lower p values). (C) Hierarchical clustering of the top 500 genes (rows) based on their relative expression levels in each sample (column). Yellow and blue indicate high and low expression levels, respectively.

FIGURE 6.
FIGURE 6.

TSLPR+ mono exhibit different phenotypic and functional properties. (A and B) Human CD14+ monocytes were stimulated with LPS for 14 h, and the expression of (A) HLA-DR and (B) CD1c was assessed by flow cytometry as MFI. (Lower panels) Representative histograms of (A) HLA-DR and (B) CD1c expression in TSLPR− and TSLPR+ mono. (C–E) Human CD14+ monocytes were pretreated with LPS for 14 h and FACS-sorted into TSLPR+ and TSLPR− mono. (C) Cells were stimulated with LPS or LPS + IL-4 for 14 h, washed, and then cultured with CFSE-labeled CD4+ T lymphocytes isolated from unrelated donors for 7 d. Unstimulated (CTRL) and PHA-stimulated (PHA) lymphocytes were used as controls. The percentage of CFSElow (i.e., proliferating) cells was assessed by flow cytometry. (D) Cells were stimulated with LPS or LPS + IL-4 for 14 h, and digital phase-contrast images were taken every 15 min with a ×20 objective. Cell movements were expressed as MSD (mean squared distance between cell positions at the end and at the beginning of the cell-tracking experiment). (E) Cells were stimulated with LPS or LPS + IL-4 for 14 h and then harvested for RNA isolation and subsequent real-time RT-PCR analysis. (F) Human peripheral blood or LPS-stimulated CD14+ monocytes were stained for CD14 and CD1c, and the percentages of CD1c− and CD1c+ among CD14+ cells were calculated. (Lower panels) Representative contour plots. (G–I) Human CD14+ monocytes were stimulated with LPS and stained for CD14, CD1c, and TSLPR. Percentage of TSLPR+ cells and TSLPR MFI were calculated in the indicated populations. (I) Representative histograms of TSLPR expression in unstained controls, CD14+ CD1c− cells, and CD14+ CD1c+ cells. Data are shown as mean + SEM (A–D, F–H, and J) or as the median, the 25th and 75th percentiles (boxes), and the 5th and 95th percentiles (whiskers) (E) of six (A, B, E–H, and J), three (C), or four (D) independent experiments. *p < 0.05, **p < 0.01, determined by two-tailed paired t test (A, D, G, H, and J), repeated measures two-way ANOVA with Sidak post hoc test (B and F), repeated measures one-way ANOVA with Tukey post hoc test (C), and Wilcoxon matched-pairs signed rank test (E).

TSLPR is preferentially expressed by a subset of CD14+ CD1c+ monocytes

The evidence of increased CD1c expression among TSLPR+ mono was rather unexpected because CD1c is commonly considered a surface marker of cDC2 (34, 35). Thus, we decided to investigate the expression of CD1c in our preparations of CD14+ monocytes by flow cytometry. Surprisingly, we found that ∼1% of monocytes in our preparations exhibited a CD14+ CD1c+ phenotype. Comparable results were obtained with LPS-stimulated monocytes (Fig. 6F). Of note, the majority of CD14+ CD1c+ monocytes expressed TSLPR upon LPS stimulation, although TSLPR was also expressed by a small percentage of CD14+ CD1c− that may significantly contribute to the population TSLPR+ mono because of the high number of CD14+ CD1c− cells in our preparations (Fig. 6G). Nevertheless, LPS-stimulated CD14+ CD1c+ monocytes expressed the highest levels of TSLPR as assessed on total CD14+ CD1c+ (Fig. 6H, 6I) or CD14+ CD1c+ TSLPR+ cells (Fig. 6J).

In vivo monocyte expression of TSLPR and CD127 in Gram-negative sepsis

So far we have characterized the signals that elicit TSLPR+ mono and the phenotypic and functional properties of this subset in vitro. To evaluate the in vivo relevance of our findings, we took advantage of a publicly available microarray (GSE46955) performed on human CD14+ monocytes isolated from patients with a diagnosis of Gram-negative sepsis (blood culture positive for Escherichia coli) and after their complete recovery (i.e., 1–3 mo after resolution), as well as healthy control subjects (41). By analyzing these data, we found that monocytes isolated from patients with Gram-negative sepsis expressed increased levels of TSLPR and CD127 mRNAs compared with healthy control subjects (Fig. 7A). Interestingly, expression levels of both genes were reduced after recovery (Fig. 7B), likely linking monocyte expression of TSLPR complex to TLR4 activation in vivo.

FIGURE 7.
FIGURE 7.

In vivo expression of TSLPR and CD127 mRNAs. (A and B) Public available microarrays (GSE46955) performed on peripheral blood human CD14+ monocytes isolated from patients during Gram-negative sepsis (sepsis, n = 7) (A and B) and following their resolution or recovery (recovery, n = 7) (B), as well as from healthy donors (healthy, n = 5) (A), were analyzed to assess TSLPR and CD127 expression levels. **p < 0.01, determined by two-tailed unpaired (A) or paired (B) t test.

Discussion

The starting point of our investigation was the responsiveness of human CD14+ monocytes to TSLP. Although we demonstrate that TSLP modulates CCL17 production, we have not fully characterized its effects on human monocytes, nor have we identified a specific response elicited by TSLP alone in the absence of IL-4. Instead, we decided to focus our attention on the characterization of TSLPR+ mono, which was an unexpected yet interesting aspect of our study. The identification of TSLPR+ mono may also contribute to a deeper understanding of human monocyte responsiveness to TSLP, because it raises the question whether TSLPR+ mono are the sole monocyte subset that can be activated by TSLP. Even more importantly, LPS induces TSLPR expression on the majority of CD14+ monocytes that coexpress the myeloid DC marker CD1c. TSLPR expression on this subset of CD14+ CD1c+ monocytes is higher compared with CD14+ CD1c− cells. Thus, the population of TSLPR+ mono is composed of CD14+ CD1c+ and CD14+ CD1c− monocytes, and it is tempting to speculate that some, if not most, of the properties we have identified for TSLPR+ mono may actually be ascribed to CD14+ CD1c+ cells. Nevertheless, the percentage of TSLPR+ mono is not only reduced by NF-κB and p38 inhibitors, but is also increased by PI3K inhibitors via activation of GSK-3. These results highlight a complex network of intracellular pathways that regulates TSLPR expression, and they also argue against the hypothesis that TSLPR+ mono derive solely from precommitted precursors. Indeed, it would be unlikely to increase the percentage of TSLPR+ mono using PI3K inhibitors if this subset originated exclusively from precommitted precursors. It is conceivable that TSLPR+ mono also emerge from LPS-stimulated CD14+ CD1c− monocytes through a stochastic process dictated by the intracellular balance between proinflammatory (e.g., NF-κB, p38, and GSK-3) and anti-inflammatory (e.g., PI3K) pathways. Once this intracellular balance has been established, it is likely to influence subsequent responses of TSLPR+ and TSLPR− mono. For example, restimulation of TSLPR− mono does not induce TSLPR expression. Moreover, it would be interesting to evaluate whether such modulation of signaling pathways also promotes the conversion of CD14+ CD1c− toward CD14+ CD1c+ monocytes. Interestingly, studies performed at the single-cell level have revealed, in contrast with population-level studies, a remarkable heterogeneity in the activation of signaling pathways and gene expression programs upon stimulation of apparently homogeneous populations (42–44). Moreover, it is now clear that even innate immune cells preserve memory of their previous stimulation (45, 46). Further studies are required to understand the relative contribution of precommitted CD14+ CD1c+ progenitors and their relationship to CD14+ CD1c− monocytes, as well as stochastic differences in the activation of signaling pathways to the emergence of TSLPR+ mono.

The existence of CD14+ CD1c+ cells (referred to as human inflammatory DCs) has been reported in several inflammatory conditions, including ovarian and breast tumor ascites (47). Inflammatory DCs induce higher CD4+ T cell proliferation and Th17 skewing compared with CD14+ CD16+ CD1c− inflammatory macrophages isolated from the same tissue, probably because of their ability to produce the Th17-polarizing cytokine IL-23 (48). While this manuscript was in preparation, the presence of CD14+ CD1c+ monocytes has been reported in the peripheral blood of healthy donors and mucosal tissues isolated from distal duodenum/proximal jejunum of pancreatic cancer patients, nasal mucosa of healthy donors or allergic patients, or bronchial mucosa obtained from patients with non-small cell lung carcinoma (49). Importantly, the frequency of this subset is elevated in the peripheral blood of stage III or IV melanoma patients and in skin melanoma lesions compared with healthy donors (50). CD14+ CD1c+ cells are less efficient at inducing CD4+ T cell proliferation compared with CD1c+ DCs (suggesting their classification as monocytes) (49, 50) and also exhibit a unique gene signature (50). We demonstrate that CD14+ CD1c+ cells express higher levels of TSLPR in response to LPS compared with CD14+ CD1c− monocytes. Interestingly, TSLP promotes myeloid DC maturation, cytokine production, and their ability to induce CD4+ T cell proliferation and polarization toward distinct phenotypes (e.g., Th1, Th2, Th17) depending on the inflammatory milieu. It will be interesting to evaluate whether TSLP exerts similar effects on CD14+ CD1c+ cells. Indeed, it is likely that this monocyte subset is the most responsive to TSLP. Further studies are warranted to assess the spectrum of responses elicited by TSLP in CD14+ CD1c+ TSLPR+ cells.

Among the list of differentially expressed genes we confirmed that TSLPR+ mono express higher levels of gene with important immune-related functions: GAS6, ALOX15B, FCGR2B, and LAIR1. GAS6 encodes the vitamin K–dependent protein GAS-6 that is mainly produced by endothelial cells, vascular smooth muscle cells, and hematopoietic cells. It binds the TAM receptor tyrosine kinases, especially AXL, and as such is involved in the regulation of inflammation, promotes tissue repair and vascular homeostasis, and modulates both cancer cell growth and tumor-associated immune cell functions (37). Of note, tumor cells promote GAS-6 production by tumor-associated macrophages that in turn promote cancer growth and metastasis (51). ALOX15B encodes the enzyme arachidonate 15-lipoxygenase B (15-LOX-B) that mainly catalyzes the conversion of arachidonate into 15(S)-HpETE, which is in turn converted to 15(S)-HETE that acts as a precursor for the synthesis of the proresolving lipid mediators lipoxins (38). FCGR2B encodes the only receptor (FcγRIIB) for the C region of IgG endowed with inhibitory properties (39). LAIR1 encodes an inhibitory receptor (LAIR-1 or CD305) for collagen or collagen-like motif-containing proteins (e.g., C1q and surfactant protein D). Its activation impairs monocyte cytokine production and differentiation toward DCs (40, 52–54). Considering these results with the increased production of CCL17 and IL-10 and the lower production of IL-6 by TSLPR+ mono, it is tempting to speculate that this subset is endowed with immunoregulatory/anti-inflammatory properties. Again, whether these properties belong to CD14+ CD1c+ TSLPR+ cells, CD14+ CD1c− TSLPR+ cells, or both subsets remains to be established.

In conclusion, by investigating human CD14+ monocyte responsiveness to TSLP, we unravel a previously unknown phenotypic and functional heterogeneity marked by differential TSLPR expression. The expression of the myeloid DC marker CD1c within the TSLPR+ mono subset revealed further heterogeneity. Indeed, peripheral blood monocytes can be divided into CD14+ CD1c− and CD14+ CD1c+ cells, the latter expressing the highest levels of TSLPR upon LPS stimulation. Considering the increased expression of TSLPR mRNA in CD14+ monocyte isolated from patients with Gram-negative sepsis, the expansion of CD14+ CD1c+ cells in the peripheral blood of melanoma patients, and their unique gene expression signature, further efforts should be made to characterize the functional properties of this subset (e.g., responsiveness to TSLP), its relationship to CD14+ CD1c− monocytes and cDC2, as well as its relevance in vivo.

Disclosures

The authors have no financial conflicts of interest.

Footnotes

  • This work was supported by grants from the Regione Campania CISI-Lab Project, the CRèME Project, and the TIMING Project (to G.M.).

  • The RNA sequencing data reported in this article have been submitted to the European Nucleotide Archive (http://www.ebi.ac.uk/ena) under accession number E-MTAB-4996.

  • The online version of this article contains supplemental material.

  • Abbreviations used in this article:

    cDC2
    conventional DC 2
    Ct
    cycle threshold
    DC
    dendritic cell
    GO
    Gene Ontology
    MFI
    median fluorescence intensity
    MSD
    mean square displacement
    RNA-seq
    RNA sequencing
    TSLP
    thymic stromal lymphopoietin
    TSLPR
    TSLP receptor
    TSLPR+ mono
    TSLPR+ monocyte
    TSLPR− mono
    TSLPR− monocyte
    UBC
    ubiquitin C.

  • Received August 30, 2016.
  • Accepted February 24, 2017.

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