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The Plasticity of Dendritic Cell Responses to Pathogens and Their Components

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Science  26 Oct 2001:
Vol. 294, Issue 5543, pp. 870-875
DOI: 10.1126/science.294.5543.870

Abstract

Dendritic cells are involved in the initiation of both innate and adaptive immunity. To systematically explore how dendritic cells modulate the immune system in response to different pathogens, we used oligonucleotide microarrays to measure gene expression profiles of dendritic cells in response to Escherichia coli,Candida albicans, and influenza virus as well as to their molecular components. Both a shared core response and pathogen-specific programs of gene expression were observed upon exposure to each of these pathogens. These results reveal that dendritic cells sense diverse pathogens and elicit tailored pathogen-specific immune responses.

How organisms respond appropriately to the wide variety of pathogens and antigens they encounter on a daily basis remains a central question in immunology. It has recently been shown that pattern recognition receptors expressed on immune cells contribute to the specific detection of pathogens (1, 2). However, the downstream target genes induced by the different pathogens have not been fully determined. The importance of dendritic cells (DCs) in initiating immune responses led us to investigate at a genetic level how DCs discriminate different pathogens (3). DCs reside in an immature state in most tissues, where they recognize and phagocytose pathogens and other antigens (4). Direct contact with many pathogens leads to the maturation of DCs, which is characterized by an increase in antigen presentation, expression of costimulatory molecules, and subsequent stimulation of naı̈ve T cells in lymphoid organs (4). The extensive reprogramming of DCs during maturation prompted us to measure the corresponding changes in gene expression. We used oligonucleotide microarrays (5) to test to what extent DCs discriminate between phylogenetically diverse pathogens and whether the commonly studied molecular components of these pathogens are sufficient to account for the live pathogen response.

Human monocyte-derived DCs (6) were exposed to a diverse set of organisms and compounds: a Gram-negative bacterial species, E. coli, and its cell wall component, lipopolysaccharide (LPS); a fungus, C. albicans, and yeast cell wall–derived mannan; and an RNA virus, influenza A, and double-stranded RNA (dsRNA). DCs were cultured (6) with pathogens or their components between 1 and 36 hours (7) and RNA was isolated, labeled, and hybridized to microarrays (8, 9). Each pathogen stimulation was repeated in three independent donors, and each component stimulation was repeated in two donors. Genes with expression levels that changed in response to stimuli (termed regulated genes) were selected on the basis of repeated differences in the expression levels of the treated and untreated samples across multiple time points (10). Of the ∼6800 genes represented on the oligonucleotide array, a total of 1330 genes changed their expression significantly upon encounter with one of the pathogens or components (10). Such a large-scale change in gene expression demonstrated that DCs are able to undergo a marked transformation in their cellular phenotype.

Analysis of the individual responses to pathogens showed that a unique number of genes was regulated by each pathogen. Influenza and E. coli were able to modulate the expression of exclusive subsets of genes (Fig. 1, A and C) (11), whereasC. albicans only modulated the expression of a subset ofE. coli–regulated genes (Fig. 1B). In addition, gene expression was most rapidly induced by E. coli, less rapidly by C. albicans, and most slowly by influenza (12).

Figure 1

Pathogen-regulated gene expression in human monocyte-derived DCs. (A) Overlapping sets of E. coli–, C. albicans–, and influenza-regulated genes (10). Numbers in the overlapping region of the Venn diagram represent common regulated genes. Numbers of pathogen-specific genes are shown inside the stippled circles (11). Some pathogen-specific genes are also found in the common group but are much more strongly regulated in one pathogen than in others. (B) Representation of mRNA expression levels at 0, 1, 2, 4, 8, 12, and 24 hours in response to E. coli and C. albicans. Each gene is represented by a single row of colored bars, and each time point is represented by a single column. Color bars represent the ratio of hybridization measurements between corresponding time points in the pathogen and control medium profiles, according to the scale shown. Genes are placed in groups corresponding to pairwise overlaps shown in accompanying Venn dia- grams. From top to bottom: E. coli– but not C. albicans–regulated genes; common regulated genes; C. albicans– but not E. coli–regulated genes. (C) Gene profiles and overlaps for E. coli and influenza. (D and E) Gene expression of common response genes [(D), see also Fig. 2] and differential response genes [(E), same genes as in Table 1] in three independent donors.

The intersection of the three different pathogen responses revealed a common set of 166 highly regulated genes (Fig. 1, A and D). To describe the dynamics of DC response after exposure to any of the three pathogens, we classified these genes according to their kinetics of expression and known biological functions (Fig. 2) (13). Immediately after contact with any of the three pathogens, a rapid decline was observed in the transcript levels of genes associated with phagocytosis and pathogen recognition (Fig. 2B). At the same time, there was a transient increase in the expression of immune cytokines, chemokines, and receptors that contribute to the recruitment of monocytes, DCs, and macrophages to the site of infection. Also strongly induced was a set of cytoskeletal genes that may potentially mediate shape change and migratory behavior of activated DCs. The induction of signaling genes and transcription factors in the middle phase may be involved in preparing the DC to be receptive to regulatory signals in the lymphatics and lymph nodes. In addition, several antigen processing and presentation genes were induced to high levels in a sustained fashion. Genes involved in generating reactive oxygen species (ROS) were induced across the time course, which suggests that infecting organisms are killed throughout DC maturation and migration. Finally, during the late phase, chemokine receptors known to mediate responses to lymph node chemokines, thereby mediating DC migration, were up-regulated (14). The set of 166 genes described here thus constitutes part of a core DC response. This response is elicited independently of pathogen characteristics and unfolds as a temporally ordered cascade that modulates both innate and adaptive immune responses (Fig. 2C).

Figure 2

Expression kinetics of common response genes in DCs. (A) Schematic transient (T) and sustained (S) gene expression profiles based on self-organizing map clusters of up-regulated genes (38). Temporal clustering of up-regulated genes is based on the expression kinetics of E. coli–responsive genes (E, early; M, middle; L, late). Down-regulated genes (down) were placed into a single cluster. (B) Function of genes regulated at different times in response to any pathogen; underlined genes are down-regulated; all others are up-regulated. GenBank accession numbers are listed in (12). (C) Stages in DC life: encounter and phagocytosis of pathogens, activation of the innate immune response, migration to the lymph node, antigen presentation and stimulation of the adaptive immune cells, and apoptosis.

In contrast, analysis of the E. coli–specific genes (Table 1 and Fig. 1E) showed that DCs also strongly and rapidly up-regulated most innate immune genes on the array, including inflammatory cytokines, neutrophil- and monocyte-attracting chemokines, and prostaglandin pathway components. This potent inflammatory response probably is partially counteracted by interleukin-10 (IL-10) that is induced in the middle phase. At later times, genes that regulate the adaptive immune response were induced, including T cell–stimulating genes, secreted cytokines, and a subset of chemokines that are thought to attract naı̈ve TH2 T helper cells (15). An unexpected class of cytokine receptors that share a common γ chain (IL-2R, IL-7R, IL-15R, and IL-4R) were also induced. The expression of these receptors may allow DCs to respond to lymphocyte-derived interleukins within the lymph node.

Table 1

Functional categories of genes regulated differentially in response to E. coli, C. albicans, and influenza. Code: +, gene expression is up-regulated in response to pathogen; −, gene expression is not changed; ++ and +++, gene expression is changed at a higher level relative to other pathogens that regulate the same gene (each + denotes increased expression by a factor of ∼2.5); +/−, gene expression is regulated in a subset of donors; d, gene expression is down-regulated.

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All these immunostimulatory responses may be enhanced through induction of additional induced gene families (Table 1) (12)—for example, cell stress genes that modulate levels of antimicrobial ROS, antiapoptotic genes that may extend the lifetime of the infected DC (16), and the late-expressing matrix metalloproteases that may allow processing of cytokines and DC migration to lymph nodes (17). Genes with undefined roles in DC function were also regulated by E. coli, including signaling molecules, transcription factors, adhesion molecules, and many of the glycolytic genes. HIF1α, a known transcription factor of glycolysis genes, was also up-regulated (18). Collectively, these diverse changes of gene expression in response to E. coli and LPS reflect a significant cellular and immunological reprogramming of the DC.

Relative to the response of DCs to E. coli, their response to C. albicans was greatly attenuated in many functional categories and constituted a subset of the E. coli response, with a much smaller number of immune genes and with no robust C. albicans–specific genes (Fig. 1, A and B, and Table 1). Because many of the immune genes are known to be regulated by the transcription factor NF-κB (19), this difference may be partially explained by the relatively weak NF-κB up-regulation (Table 1).

DCs regulated a large number of genes in response to influenza, comparable to the number regulated in response to E. coli. However, the innate immune response was relatively weak and completely devoid of genes capable of stimulating neutrophils, as confirmed by a neutrophil chemotaxis assay (12). The adaptive response to influenza was also distinct from the response to E. coli. The antiviral genes—those encoding interferon (IFN) α and β—were strongly induced, as were the interferon-inducible chemokine genes (Table 1). This suggests possible effects on induction and migration of naı̈ve TH1 cells (15). An important subset of genes induced by influenza are linked with the inhibition of the immune response at certain stages. These include proapoptotic genes that may lead to early death of infected cells (16) as well as genes encoding mcp-1, which can block IL-12 production in macrophages (20); HLA-E, which can inhibit natural killer cells (21); Gfrp, a close homolog of a protein that inhibits NO synthesis (22); and IDO, which can inhibit T cell activation (23). Influenza also modulated the expression of a large set of genes involved in diverse cellular functions and whose contribution to pathogen-host interactions may not have been studied previously (12).

To further dissect the ability of DCs to discriminate pathogens, we investigated whether individual pathogen components were sufficient to elicit these differential pathogen responses. Despite additional active molecules known to be present on bacteria, LPS was able to mimic and account for almost the entire bacterial response (Fig. 3A). Unexpectedly, the fungal component mannan mimicked the magnitude and biological character of the bacterial response more closely than it did the fungal or viral response profiles (Fig. 3, A and B) (12). Although dsRNA was a less potent stimulator of the bacterial response, it did elicit a strong innate response comparable to that induced by bacteria, and at the same time elicited aspects seen in the viral response (Fig. 3, A and B) (12). Thus, all three components were able to elicit the expression of many innate immune genes as well as most of the genes in the common pathogen response. This finding shows that the core DC program can be triggered by multiple stimuli with diverse molecular structures.

Figure 3

Relation between pathogen- and component-responsive genes. (A) Overlapping sets of pathogen-regulated and corresponding component-regulated genes (as in Fig. 1). (B) Comparison of E. coli–regulated and other component-regulated genes.

Genome-scale studies of DC transcriptional responses have allowed us to demonstrate the existence of common and differential pathogen recognition pathways. Although there have been reports of changes in gene expression in DCs in response to LPS, the response to pathogens has not been thoroughly investigated (24, 25). Differential immune responses to pathogens have been described in clinical and animal studies (26–28), and we show here that these responses are reflected by changes in DC gene expression.

The temporal cascade of gene expression in the common response to pathogens [which is also induced by Gram-positive Staphylococcus aureus (29)] accounts for core DC functions and delineates the essential role of DCs in linking innate recognition of pathogens with antigen presentation and the development of an adaptive T cell response (30–33). The existence of this common response reflects a convergence of pathways from receptors that are known to distinguish some of these components and pathogens. In contrast, the presence of pathogen-specific gene expression in most functional categories (including transcription factors and cytokines) suggests that distinct pathways are activated by different pathogens. These differential responses demonstrate that human monocyte-derived DCs are flexible in their responses and may even exhibit a diversity of responses similar to that of the different DC subtypes (34,35).

The extensive plasticity of the DCs observed in our experiments indicates that the concept of DC maturation cannot be simply defined by the modulation of a standard set of markers (4). Instead, we propose that DCs not only are capable of generating a core response to any pathogen, but also exhibit stimulus-specific maturation and activation. For each stimulus, particular subsets of genes are modulated and lead to important physiological consequences. There is likely to be even more differential regulation in vivo, depending on DC subtype, cell interactions, and tissue location. Determining whether these unique responses are advantageous to the pathogen, or to the host, is essential for understanding host-pathogen interactions (36). Further studies of these pathogen-regulated genes may thus enhance our understanding of DC maturation and provide future targets for immunotherapy.

  • * To whom correspondence should be addressed. E-mail: hacohen{at}wi.mit.edu

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