The global transcriptional maturation program and stimuli-specific gene expression profiles of human myeloid dendritic cells
Davorka Messmer1,
Bradley Messmer1 and
Nicholas Chiorazzi1
1 Laboratory of Experimental Immunology, North ShoreLong Island Jewish Research Institute, and The Departments of Medicine North Shore University Hospital and NYU School of Medicine Manhasset, NY 11030, USA
The first two authors contributed equally to this work
Correspondence to: D. Messmer, North ShoreLIJ Research Institute, 350 Community Drive, Manhasset, NY 11030, USA.E-mail: dmessmer{at}nshs.edu
Transmitting editor: R. Steinman
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Abstract
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Dendritic cells (DC) are central to the immune response against invading pathogens. How DC translate different signals received from either other components of the immune system or from pathogens into a tailored immune response is not understood in detail. Using oligonucleotide microarray technology we performed a genome-wide analysis to investigate the transcriptional program in immature human monocyte-derived DC induced to mature with either CD40 ligand (CD40L), lipopolysaccharide (LPS) or a cocktail of inflammatory cytokines and prostaglandin (PG) E2 (CyC). We identified elements of a sustained common response to LPS and CyC, as well as sets of transient and stimulus-specific gene expression changes. Interestingly, the transient LPS response as well as the sustained LPS-specific response included a high number of chemokines, suggesting that LPS stimulation of DC leads to enhanced recruitment of immune cells and potentially prolongs the immune response compared to an inflammatory signal mimicked by CyC. Of note, the core response common to both LPS and CyC comprised a high number of unknown genes as well as genes that have not been previously identified as part of the maturation response in DC. Since some of these genes have down-regulatory functions in other settings, they may have a regulatory role in DC maturation and immune response generation.
Keywords: activation, CD40 ligand, gene expression profile, inflammatory cytokines, lipopolysaccharide, prostaglandin E2
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Introduction
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Dendritic cells (DC) are central to the immune response against invading pathogens. DC play a key role in initiating, shaping and controlling the immune response. Classically, their primary function is to present antigen to T cells, but DC can also interact with other members of the immune system through surface molecules and cytokines. DC can be functionally divided into immature and mature cells based on their capacity to stimulate T cells, a property of mature DC (1). This functional maturation correlates with surface expression of high levels of MHC class II molecules, adhesion molecules (CD54 and CD58) and co-stimulatory receptors (CD80 and CD86) (24) as well as decreased antigen uptake capacity (CD206).
While the antigen-presenting function of DC is central, the concordant immunological effector functions are dependent on additional variables. Distinct DC subsets have been documented and can regulate the immune response differently (5). There is also growing evidence that DC subsets can differ in their responses based on microenvironmental changes or pathogens and their products (68). It has been suggested that DC play the role of central processing unit of the immune system, whereby different stimuli lead to a qualitatively different maturation outcome (9). In support of this idea are studies showing that myeloid DC that encounter different stimuli secrete distinct sets of cytokines (10,11).
Recently, highly parallel expression analyses by microarrays have begun to elucidate the genetic pathways of DC maturation. An early study addressed the expression of 4110 known genes upon DC maturation induced by a cocktail of inflammatory cytokines and prostaglandin (PG) E2 (12). Granucci et al. analyzed the response of a murine DC cell line (D1) to Escherichia coli (13) as well as to lipopolysaccharide (LPS) and tumor necrosis factor (TNF)-
(14). The strongest support for the notion that DC are plastic in their maturation responses came from Huang et al. (15), who performed kinetic analyses of human monocyte-derived DC stimulated with pathogens and their components, using an early generation Affymetrix Genechip oligonucleotide microarray which contained probes for
6800 genes. From this subset of the human expression genome, these investigators demonstrated distinct gene expression patterns in response to different pathogen-derived stimuli.
We analyzed the gene expression changes in immature human monocyte-derived DC (myeloid lineage) matured with a cocktail of inflammatory cytokines and PGE2 (CyC) versus those induced to mature with LPS and versus soluble CD40 ligand (CD40L), using the HG-U95 series Genechip (Affymetrix) oligonucleotide microarrays. These arrays contain >60,000 unique probesets to detect known genes and ESTs, providing nearly complete coverage of the expressed genes in the human genome (16). Over 1000 genes comprising a generic maturation program common to LPS and CyC were defined. In addition, distinct patterns of expression for DC populations matured with CyC versus LPS were observed, both transiently (24 h) and in the final mature DC (48 h). These stimuli-specific expression patterns are direct evidence that DC process environmental signals and activate different transcriptional programs in response to distinct stimuli. The presence of numerous chemokines among the LPS-specific genes suggests an immuno-recruitment function not found in DC activated by inflammatory cytokines.
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Methods
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Generation of DC
DC were generated from peripheral blood mononuclear cells (PBMC). Blood from normal volunteers was purchased from the Long Island Blood Services (Melville, NY). The mononuclear cell fraction was isolated by Ficoll-Hypaque (Pharmacia Biotechnology, Uppsala, Sweden) density gradient centrifugation. CD14+ monocytes were isolated from PBMC by two rounds of positive selection using anti-CD14 beads (Miltenyi Biotech, Auburn, CA) following the manufacturers instructions; these cells were > 99% CD14+ as determined by flow cytometry. To generate DC, CD14+ cells were cultured in RPMI 1640 medium supplemented with 2 mM L-glutamine (Gibco/BRL Life Technologies, Grand Island, NY), 50 µM 2-mercaptoethanol (Sigma, St Louis, MO), 10 mM HEPES (Gibco/BRL Life Technologies), penicillin (100 U/ml)streptomycin (100 µg/ml) (Gibco/BRL Life Technologies) and 1% human plasma pooled from several healthy laboratory donors (heparinized). Cultures were maintained for 7 days in six-well trays (3 x 106 cells/well) supplemented with 1000 U/ml granulocyte macrophage colony stimulating factor (Immunex, Seattle, WA) and 200 U/ml IL-4 (R & D Systems, Minneapolis, MN). The cytokines were added to the cultures at days 0, 2, 4 and 6.
Stimulation of DC
Four independent experiments were performed with DC generated from four different donors. After 7 days in culture, the immature DC were transferred to new six-well plates. DC from the same donor were either left untreated (medium control) or stimulated with either 100 ng/ml LPS (E. coli serotype 026:B6; Sigma) or with monomeric CD40L [50% of the culture medium was exchanged with a supernatant from a CD40L-secreting J558L hybridoma cell culture (17) provided by Dr Peter Lane (UK)] or with CyC consisting of 1000 U/ml IL-6 (R & D Systems), 10 ng/ml TNF-
(R & D Systems), 10 ng/ml IL-1ß (R & D Systems) and 1 µg/ml PGE2 (P-5640; Sigma).
Analysis of DC phenotype
DC phenotype was monitored by flow cytometry for each experiment. DC (1 x 104) were reacted in 100 µl PBS/5% FCS/0.1% sodium azide (staining buffer) with phycoerythrin (PE)-conjugated IgG mAb (Becton Dickinson, San Jose, CA) specific for HLA-DR (Beckon Dickinson) and CD83 (PN IM2218; Immunotech-Beckman-Coulter, Marseille, France) or FITC-conjugated IgG mAb specific for CD86 (PharMingen, Los Angeles, CA) for at least 20 min at 4°C. Cells were then washed 4 times with staining buffer, fixed in 10% formaldehyde in PBS (pH 7.27.4) and examined by flow cytometry using a FACScan (Becton Dickinson). In all experiments, isotype controls were included using an appropriate phycoerythrin- or FITC-conjugated irrelevant mAb of the same Ig class.
Measurement of cytokines and chemokines
The production of cytokines and chemokines in the cell culture supernatants was measured by ELISA (Pierce Boston Technology Center, SearchLight Proteome Arrays Multiplex Sample Testing Services, Woburn MA) at the indicated time points after activation.
RNA preparation and microarray hybridization
Cells were harvested 24 and 48 h after stimulation. Total RNA from DC was immediately isolated with the RNeasy kit from Qiagen (Valencia, CA) according to the manufacturers instructions. Between 1 and 2 x 106 DC yielded
10 µg total RNA and 5 µg was sufficient for further synthesis. Double-stranded cDNA was synthesized from total RNA using a T7-polyT primer and the SuperScript Choice System Kit (Gibco/BRL). cDNA was purified by phenolchloroform extraction. Biotinylated cRNA was synthesized by in vitro transcription using the Bio Array High Yield RNA transcript labeling kit (ENZO, Farmingdale, NY). The cRNA was purified and DNase treated using the RNeasy kit (Qiagen), then fragmented according to the Affymetrix protocol and 15 µg of cRNA were hybridized to U95A-E microarrays (Affymetrix, Santa Clara, CA) overnight. Arrays were analyzed on Affymetrix scanners.
Data processing
Microarray image files (.cel) were analyzed using Affymetrix Microarray Suite (MAS) 5.0 and DCHIP 1.1 software (18). Present/absent calls were generated with MAS using the default program settings for all probesets (n = 62,981). Model-based expression values and SE were calculated using DCHIP, following normalization via program defaults. Probesets called outliers by the model-based expression were treated as blank values. Probesets that were not called present in at least two samples of the four independent experiments were not considered further. This resulted in a filtered data set of 22,513 probesets. The expression values, SE of the expression value and present/absent calls for these probesets were compiled to a single file and further analyzed using DCHIP.
Data analysis
A scoring system was created to evaluate the significance of changes in expression of genes relative to the paired immature control. First, the lower bound of the 90% confidence interval of the fold changes was computed for each gene relative to that for the immature DC. The 90% confidence interval is calculated with the DCHIP software using the SE from the model-based expression values. The lower bound of this confidence interval is thus a more stringent measure of fold change that accounts for error in the individual expression measurements. The fold changes for all of the experiments were log transformed to base 2 and averaged. The maximum deviation of the log-transformed 90% confidence interval from the average was calculated for each gene and experiment, and these log residuals were averaged to provide an estimate of the variance of the data. The score given to the fold change of a gene was defined as the square root of the product of the average fold change x (average fold change variance). This scoring system rewards data that were most consistent and includes a penalty for variance among the experiments. Genes with a score >1 (roughly equivalent to a 2-fold change) were considered significantly different between conditions, unless otherwise noted.
Hierarchical clustering was performed with Pearson correlation with average linkage as implemented in DCHIP. Data were visualized using colorimetric matrices that color code expression values based on their difference, in SD, from the mean expression value of that gene. Red colors indicate relative over-expression and blue colors indicate relative under-expression of a given probeset.
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Results
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Generation and in vitro maturation of DC
Immature DC were produced in vitro from normal human monocytes (>99% pure CD14+ cells at the initiation of culture) isolated from peripheral blood. Because some monocytes did not differentiate into DC and the number of cells that remained attached to the plate varied among donors, remaining cells were a potential confounding variable. We therefore transferred the differentiated non-adherent cells to new culture plates to eliminate these contaminating cells. It has been reported that transferred cells undergo at least partial maturation (19). Therefore, we compared the stimulatory capacity of transferred and non-transferred immature DC in an allogeneic mixed lymphocyte reaction and found that the transferred immature DC were less stimulatory than the non-transferred immature DC, suggesting that significant partial maturation had not occurred (data not shown). Therefore, in subsequent experiments the immature DC populations were transferred to fresh six-well plates on day 7, before adding the various maturation-inducing stimuli.
Immature DC generated from a single donor were treated with either LPS, CD40L or CyC (see Methods), or they were maintained as immature DC in medium. CyC has been shown to induce full DC maturation and is a more reliable replacement for the previous traditional maturation stimulus, monocyte-conditioned medium (20,21). The surface phenotype of the medium-treated controls remained unchanged and typical of immature DC, while the stimulated samples showed increased expression of maturation markers (Fig. 1A). All three stimuli consistently induced increased expression of HLA-DR, CD83 and CD86, although CD40L induced a smaller increase in CD83. Also the supernatants from the stimulated DC cultures contained significantly increased amounts of the secreted cytokines IL-6, IL-8, TNF-
and IL-12 (p70) (Fig. 1B), reflecting functional maturation. CD40L induced lower levels of IL-6, IL-8 and TNF-
, but comparable levels of IL-12.

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Fig. 1. DC maturation. (A) Phenotypic analysis of immature DC (solid curve) or DC matured with CyC (thick grey curve)-, LPS (thick black curve)- or CD40L (thin black curve)-stimulated DC. DC were analyzed for expression of the indicated surface molecules by staining with fluorescently labeled antibodies and fluorescence was quantitated by flow cytometry. (B) Cytokine levels in the DC culture supernatants 48 h after stimulation. Data shown are from three of the four donors used for the array analysis. The supernatants were collected immediately prior to RNA isolation from the cultured cells.
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Analysis of gene expression in myeloid DC
Gene expression level profiles were generated from treated and control DC harvested 24 and 48 h after transfer and stimulation. Four independent experiments were performed in which immature DC populations were generated from a single donor and split at the time of transfer for each of the experimental conditions. Different donors were used for each of the four experiments. Expression profiles were generated on the five chips that comprise the U95 Genechip series that display >60,000 unique probesets for genes and ESTs. In the subsequent descriptions, the term gene will be used in place of probeset for clarity, with the caveat that there will be redundancy when multiple probesets detect the same gene.
Genes and ESTs called present in more than two samples or time points were considered further (n = 22,513). A scoring system that considers both the magnitude of the gene expression changes as well as the consistency of those changes across the experiments was implemented (see Methods). In essence, this scoring system compensates for limited sample numbers by using a stringent lower bound estimate of the measured fold change in expression levels. Expression levels for genes whose variability was greater than their average fold changes were scored as zero.
Transcriptional responses of DC to maturation stimuli
Since by phenotypic criteria the medium control DC remain essentially unchanged over the 48 h culture period, we anticipated very few expression level changes. When the gene expression values of the medium controls at the 24 h time point were compared with those at 48 h, virtually no genes passed our significance score threshold represented by the V-shaped lines (Fig. 2A). Thus, the comparison of the medium controls at the two time points serves as an internal reference for gene expression fluctuations independent of specific maturation.
Next, the gene expression levels from the various treatment conditions were compared to the corresponding medium-treated control, and the relative fold change and significance score computed. The scatter plots in Fig. 2(BD) show the distribution of fold changes and variance relative to the medium controls for all 22,513 filtered genes for each of the stimulating conditions. These plots clearly show that CyC altered expression of the greatest number of genes and that CD40L had a greatly attenuated effect, even though all stimuli induced maturation as defined by specific changes in cell-surface molecule display and cytokine secretion (Fig. 1). The hierarchy of potency in inducing gene expression changes was CyC > LPS > CD40L (Fig. 2 and Table 1).
Analyses of gene expression changes of surface molecules and cytokines associated with DC maturation
Prior to more global analysis, we compared the gene expression changes of a panel of surface molecules and cytokines known to be altered with DC maturation, including those analyzed above. As anticipated, mRNA levels of CD205, CD86, CD83, CD80, CD58, CD54, CD40 and CD25 increased with stimulation, and CD206 levels decreased (Fig. 3A). In addition, mRNA levels of IL-6, IL-8 and IL-12ß increased, while TNF-
levels were high in unstimulated as well as stimulated DC (data not shown). The secreted protein levels and corresponding mRNA levels of IL-6 and IL-8 strongly correlated (Fig. 3B, R = 0.956 and 0.888 respectively). TNF-
levels in culture supernatants of LPS-treated DC were 23 orders of magnitude greater compared to CD40L- or medium-treated controls, despite the measurement of roughly equal mRNA levels. There was no correlation between protein and mRNA levels of TNF-
. This could be explained by LPS-induced release of TNF-
protein from intracellular compartments or post-transcriptional control mechanisms. TNF-
secretion in CyC-treated samples could not be ascertained since TNF-
is a component of the cocktail. Even though we detected increased levels of IL-12 (p70) with all three stimuli, IL-12
was not detected by microarray and the measured IL-12 (p70) levels did not correlate with the increase in IL-12ß mRNA levels (R = 0.346; Fig. 3B).

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Fig. 3. Transcriptional response of DC to maturation stimuli. The fold change and variance for the 22,513 filtered genes are shown. The lines delineate a score of 1 or 1 to the right or left of the origin respectively. Genes further from the axis than the line have a score >1 or < 1 and are considered significantly different from the medium control. (A) Medium control at 48 h compared to medium control at 24 h. (B) CD40L-stimulated DC compared to medium control. (C) LPS-stimulated DC compared to medium control. (D) CyC-stimulated DC compared to medium control. For (B)(D): solid circles, 24 h; open circles, 48 h.
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Analyses of gene expression changes induced by CD40L
A highly limited change in gene expression was observed upon stimulation with CD40L compared to the other stimuli (Table 1). Stimulation of DC with soluble monomeric CD40L induced changes in only 40 genes that were also changed by the other stimuli. Compared to the other stimuli this is a very restricted response. There were no robust changes solely in response to CD40L.
Patterns of transcription responses to LPS and/or CyC
As CD40L induced a restricted number of gene expression changes, we focused on the similarities and differences among the gene expression changes induced by LPS and CyC. The 22,513 genes were assigned to one of the 16 possible behavioral patterns based on the time point and stimulus in which they were significantly changed, if any (Fig. 4). We grouped together genes for which expression increased or decreased under the same set of circumstances. For instance, genes that were up- or down-regulated compared to medium control with CyC, but not LPS, at 24 h are shown in Fig. 4(B1). Genes that were altered with both CyC and LPS at 48 h are shown in Fig. 4(C3). The vast majority (21,073) did not significantly differ in expression from the medium-treated controls under any circumstance at 24 or 48 h (Fig. 4A1). Those genes are located between the two parallel lines have a score of <1 and are not significantly different from the medium control.

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Fig. 4. Patterns of transcriptional responses to LPS and CyC. Genes were sorted into 16 categories based on the pattern of significantly altered expression. Each panel represents a set of genes that were significantly altered (score >1 or < 1, shown as dashed lines) under the same experimental conditions. The number of genes represented in each panel is shown in the top right of the panel and the asterisks indicate the experimental condition(s) changed in that panel.
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Transiently altered gene expression
A set of genes whose expression changed at 24 h, but not at 48 h, was observed (Fig. 4A2, B1 and B2). This set was refined to those genes that exceeded the significance score threshold when compared to medium controls at 24 h, but not at 48 h, and had a scored difference between the 24 and 48 h samples that was greater than the equivalent of a 1.5-fold change. Sixty-six of the 217 probesets met these criteria (Fig. 5), of which eight were known redundancies (multiple probesets for a unique gene). No genes were transiently decreased with LPS or with both LPS and CyC. Hierarchical clustering of the expression levels of these genes identified close relationships among them. In particular, among the genes transiently increased with LPS was a closely clustered group that included a number of IFN-inducible genes (ISG15, IFIT1, MX1, OAS2, IFI44 and IFITM1). The chemokines MIP-1
, MIP-1ß, and MCP-2 also clustered tightly, and were transiently increased with LPS.

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Fig. 5. Transiently altered gene expressions. Genes shown satisfied two criteria. First, they were significantly different in the stimulated DC compared to medium control only at 24 h. Second, they were scored as significantly different between 24 and 48 h. Standardized expression values are colorimetrically represented according to the scale at the bottom, with units being SD from the normalized mean. The dendrogram to the left represents a hierarchically clustered tree using a Pearson correlation with average linkage. The four columns of colored data under each stimulus at each time point represent the results of individual experiments. Gene names are shown at right. The HGNC symbol followed by the gene name is shown; if no name has been assigned, the GenBank accession number is provided. Red colors indicate relative over-expression and blue relative under-expression of a given gene. Black represents poor data quality from the microarray that was excluded from analysis.
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Sustained gene expression changes in mature DC as a function of LPS and/or CyC stimulation
Genes that displayed significant changes relative to medium control at 48 h (Fig. 4A3-4, B3-4, C1-4 and D1-4) were divided into three categories: common gene expression changes that represent the core DC maturation program, stimulus-biased gene expression changes and stimulus-specific gene expression changes (Fig. 6A).

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Fig. 6. Comparison of the gene expression changes in response to CyC and LPS. (A) Genes that were significantly altered at 48 h with either stimulus are plotted. The triangles and squares represent genes that were stimulus specific (scored as described in Methods), with triangles representing genes specifically up- or down-regulated with CyC and squares representing genes up- or down-regulated with LPS. The region that contains the core response genes is indicated by the lines, with the core response genes as solid circles. Genes whose expression change scores were biased with one stimulus are indicated by open circles. (B) Colorimetric matrix representation of core response genes. Expression values at 48 h are shown for medium control, CyC- and LPS-stimulated samples. (C) Colorimetric matrix representation of biased genes. Genes with known functions from (B) and (C) are categorized in Table 2.
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A gene was classified as part of the core maturation response if the scores from both stimuli compared to medium controls were within 2-fold of each other (Fig. 6A, solid circles). The 752 genes that satisfied this criterion are shown hierarchically clustered in Fig. 6(B). In total, 369 genes were classified as biased (Fig. 6A, open symbols), i.e. reflecting their relatively greater expression compared to medium control, but not specifically different (as defined below) in expression in response to one stimuli or the other (Fig. 6C). For example, a gene that is increased 2-fold with one stimulus and 6-fold with the other stimulus is considered a gene with biased expression during maturation induced by the two stimuli. Of the 1121 genes that comprise the core and biased categories, 423 were known genes with some functional annotation in the public databases. These are grouped into functional categories in Table 2.
A change in gene expression was considered specific if it was scored significantly different with one stimulus, but not the other, when compared to medium controls, the difference in scores relative to medium control was >2-fold, and the score when compared to the other stimulus was also significantly changed (Fig. 6A; red and blue symbols). It should be noted that this stringent definition of a stimulus-specific change in gene expression is weighted towards those genes whose expression is uniquely induced by one stimulus as opposed to those with quantitatively different levels of induction. Ninety-one unique genes satisfied the stimulus-specific criteria. The majority of these (75 of 91) were specifically changed in response to CyC (69 genes increased and six decreased). Nine genes were specifically increased in response to LPS, four of which were chemokines (MIP-3ß, DC-CK1, MPIF-1 and RANTES). Seven genes were specifically decreased after stimulation with LPS. Hierarchical clustering of the 48-h expression changes associates these genes as expected (Fig. 7), with the major branches representing the stimulus-specific genes annotated on the scatter plot in Fig. 6(A).

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Fig. 7. Stimulus-specific genes. Colorimetric matrix showing expression values at 48 h for medium control, CyC- and LPS-stimulated samples. The branches of the dendrogram on the left that group the genes into stimulus-specific up- or down-regulations are labeled with the appropriate symbols from Fig. 6(A).
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Discussion
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In this study we determined the genes whose expression changed, either positively or negatively, during the in vitro induced maturation of DC from an immature to a mature stage. We separately considered CD40L-, LPS- and CyC-induced maturation. These stimuli had differential effects on gene expression, even though all induced phenotypic and functional maturation as defined by specific changes in cell-surface molecule display and cytokine secretion. The hierarchy of potency in inducing gene expression changes was CyC > LPS > CD40L. It was surprising that CyC induced approximately twice as many significant gene changes as LPS, especially since LPS induces the secretion of all of the cocktail components: TNF-
, IL-1ß, PGE2 and IL-6. However, the amounts of those cytokines induced by LPS, the timing of their secretion in relation to the duration of maturation and cell culture, signaling through the LPS receptor complex (22), as well as the release of other factors could account for response to the monomeric the differences in gene expression profiles.
Stimulation of DC with soluble monomeric CD40L induced changes in only 40 genes. Compared to the other stimuli, this is a very restricted response. Since CD40L-expressing cell lines (23,24) and soluble trimeric CD40L (25,26) are known to induce DC maturation, the restricted maturation response that we detected is most likely due to the monomeric nature of the CD40L that we used in our culture system. However, since the measured IL-12 (p70) levels in the DC supernatant activated by the soluble CD40L monomer (Fig. 1) are comparable to levels detected using the CD40L trimeric molecule (27), and the phenotypic markers up-regulated by CD40L were comparable to LPS and CYC, the trimeric nature of CD40L might not be required for these changes. Nevertheless, soluble trimeric CD40L has still been shown to be inferior to CyC and LPS for maturation of macaque DC (28). Furthermore, a second signal provided by IFN-
or LPS was shown to enhance IL-12 production by DC (27,29). Interestingly, memory Th cells, but not naive Th cells, induce IL-12 production in DC (29). Since other T cell factors are required for full DC maturation, soluble CD40L alone (either monomeric or trimeric) is not a physiological representation of T cell-induced DC activation. Therefore, it would be interesting to analyze the gene expression profile of DC cultured with naive or memory T cells and also to analyze the synergistic effects of CD40L with other stimuli like LPS.
We divided the altered gene expression changes induced by LPS or CyC into transient and sustained responses. The sustained gene expression changes were divided into three categories: common gene expression changes, stimulus-biased gene expression changes and stimulus-specific gene expression changes.
Transient gene expression changes
Genes coding for chemokines, CCL3 (MIP-1
), CCL4 (MIP-1ß) and CCL8 (MCP-2), were found to be transiently up-regulated with LPS at 24 h, but not 48 h (Fig. 6). The secretion of these chemokines could enhance recruitment of monocytes by CCL3, CCL4 and CCL 8, T cells by CCL3 and CCL4, DC by CCL3, and NK cells by CCL8 and other cell types. The transient up-regulation of CCL3 and CCL4 correlated with the reported up-regulated on the RNA level in response to LPS (30). However, we found CCL8 up-regulation transient and not sustained (30).
In addition, genes for six IFN-induced proteins were transiently up-regulated by LPS (Fig. 5). Type I IFN are potent anti-viral substances that also influence the release of pro-inflammatory cytokines and NO by DC (31). Type I IFN are secreted by LPS-stimulated DC, which renders DC more resistant to influenza infection (32). One of the six transiently up-regulated, IFN-induced genes was MxA (M33882), confirming a previous report that MxA is expressed in DC in response to LPS stimulation, but not to monocyte-conditioned medium (33), which can be mimicked by CyC. The other IFN-induced genes that were transiently up-regulated in response to LPS stimulation have not been previously described as being expressed in DC. These genes might play a role in anti-viral or anti-bacterial defense. Three known and five unknown genes clustered tightly with the IFN-induced genes (Fig. 5, see dendrogram), indicating that those genes are co-regulated. This indicates a highly regulated IFN response in DC and suggests that the other genes that are part of this cluster could play a role in the IFN response in DC.
Among the genes that were transiently altered in response to CyC was adenosine deaminase (ADA). ADA controls cAMP production, that in turn can induce apoptosis if its levels are high (34). Since DC maturation is accompanied by the expression of survival molecules (35,36), the CyC-induced increase in ADA gene expression might reflect part of the anti-apoptotic response induced by maturation stimuli. Furthermore, ADA reverses adenosine-inhibited adhesion of polymorphonuclear leukocytes to the vascular endothelium (37) and could play a similar role in enhancing the adhesion of mature DC.
The hepatocyte growth factor receptor is also transiently up-regulated after CyC treatment. Binding of hepapoietin A/scatter factor, the hepatocyte growth factor receptor ligand, results in increased survival of endothelial cells (38). Furthermore, ligand-activated receptor regulates DC adhesion to the extracellular matrix component, laminin (39). Interestingly, both scatter factor and laminin were specifically increased at 48 h after CyC stimulation. Signaling through the hepatocyte growth factor receptor might contribute to CyC-induced DC survival and enhance the attachment of CyC-matured DC to the extracellular matrix of the lymphoid tissue.
Common core gene expression changes
We found CD200 (OX2) among the common genes up-regulated with both LPS and CyC. CD200 is expressed on DC in the follicles of spleen and lymph nodes (40). It provides a negative signal, decreasing macrophage and myeloid cell activity (41), and triggers an immunomodulatory function which leads to increased allograft survival (42). Our documentation that CD200 is up-regulated upon DC maturation could indicate a regulatory mechanism to put a brake on the DC immunostimulatory capacity in order to limit the intensity or duration of a resulting immune response. Thus, the induction of DC maturation pathways might be followed by an induction of inhibitory pathways to the immune response. Further support for this idea is our finding of the up-regulation upon DC maturation of the third co-stimulatory molecule of the B7 family (B7-H1) (Table 2, adhesion), which may be involved in the negative regulation of cell-mediated immune responses (43,44).
Interaction of DC with T cells is crucial for the induction of an immune response. Upon DC maturation, several adhesion molecules are up-regulated on the cell surface (45). On the transcriptional level, we found up-regulation of CD54, CD58, integrin ß8 (ITGB8), endothelial differentiation, sphingolipid G-protein-coupled receptor1 (EDG1) and CD42b (GP1BA) by LPS and CyC. Interestingly, 15 genes associated with cell adhesion were down-regulated with both stimuli on the RNA level. This might represent an additional inhibitory control on the immune response once DC are mature, as suggested by the up-regulation of the negative regulators mentioned above.
Biased gene expression changes
In addition to the common core genes and the stimulus-specific genes (see below), a large number of genes were identified that were categorized as biased and might play a significant role in DC maturation (Fig. 6C and Table 2). However, discussion of this large set of genes must await more detailed studies.
CyC-specific gene expression changes
We identified a large number of genes whose expression was specifically altered by CyC at 48 h, when DC are considered mature. The majority of these genes were up-regulated. Many of these CyC-induced genes have known (cell adhesion, apoptosis, vesicular transport and migration) as well as undefined roles in DC function (Fig. 7). Of the genes known to be involved in T cell activation that are specifically up-regulated by CyC were OX40L and IL-12ß (p40). Interestingly, IL-12
(p35) was not detected. It has been shown that p40 mRNA is up-regulated in the cells producing IL-12, whereas p35 mRNA is constitutively expressed (46). The CyC-induced up-regulation of p40 is in concordance with those results. However despite this restriction in mRNA changes induced by CyC, activation of DC with either CyC or LPS led to the secretion of the bioactive protein form of IL-12 (p70; Fig. 1). This lack of correlation could result from post-transcriptional regulation, intracellular accumulation, heterodimer partner limitation or autocrine adsorption.
LPS-specific gene expression changes
Interestingly, a substantial fraction of the LPS-induced genes were chemokines (seven of 34). Three chemokine genes were transiently induced by LPS at 24 h. Furthermore, four of the nine genes that were specifically up-regulated with LPS at 48 h encode chemokines: CCL5 (RANTES), CCL19 (MIP-3ß), CCL18 (DC-CK1) and CCL23 (MPIF-1). LPS has been shown to induce CCL5 expression in a mouse DC line (47), and increase mRNA levels for CCL19 and CCL18 in monocyte-derived DC (30). Our data confirm these results and further show that the up-regulation of CCL5, CCL18, CCL19 and CCL23 (Fig. 7) is LPS specific compared to CyC.
Taken together, these data suggest that DC that have detected pathogen (but not those matured by inflammatory signals) might enhance the recruitment of mature T cells by CCL19 (48), naive T cells by CCL18 (49), memory T cells by RANTES (50), DC by CCL2 and CLL5 (51,52), monocytes by CCL23 and CCL5 (53), NK cells by CCL5 (54,55), and other immune cells to the site of infection, leading to an amplification of the immune response against the invading pathogen. The lack of enhanced immune cell recruitment after maturation in response to a mix of inflammatory cytokines and PGE2 might reflect adaptation to prevent an uncontrolled response toward self induced by DC in the absence of an infection, since a danger signal (56) provided by pathogens or their components would be lacking. In this regard, the core maturation response shows a set of genes that is not stimulus-specific and might represent genes that control the functional features of mature DC, such as antigen processing and presentation, co-stimulation, etc. Conversely, the stimulus-specific response, especially the LPS-specific changes in gene expression, may involve pathogen-specific pathways that could be either of advantage for the bacteria or induced by the DC in order to fight the infection, either directly or by activating other immune cells.
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Acknowledgments
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We would like to thank Dr Leslie Goodwin, Milka Rodriguez and Sarah Courtney for their technical assistance with the microarray experiments, and Catherine Rapelje for FACS analyses. We thank Drs. Melissa Pope, Sylvie Beaulieu, Garry Peretz and Kirk Manogue for critical reading of the manuscript. This work was supported by grants from the NIAID (AI 10811) and from the NCI (CA 81554 and CA 87956).
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Abbreviations
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ADAadenosine deaminase
CD40LCD40 ligand
DCdendritic cells
LPSlipopolysaccharide
PBMCperipheral blood mononuclear cell
PEphycoerythrin
PGprostaglandin
TNFtumor necrosis factor
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