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Physiol. Genomics 25: 75-84, 2006. First published December 13, 2005; doi:10.1152/physiolgenomics.00188.2005
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Received 27 July 2005; accepted in final form 6 December 2005.
Physiological Genomics 25:75-84 (2006)
American Physiological Society © 2006 American Physiological Society

Role of strain differences on host resistance and the transcriptional response of macrophages to infection with Yersinia enterocolitica

Katrin van Erp, Kristina Dach, Isabel Koch, Jürgen Heesemann and Reinhard Hoffmann

Max von Pettenkofer-Institut, Department of Bacteriology, Munich, Germany


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 GRANTS
 REFERENCES
 
The outcome of a host-pathogen encounter is determined by virulence factors of the pathogen and defense factors of the host. We characterized the impact of host factors [resistant (C57BL/6) or susceptible (BALB/c) genetic background and exposure to interferon (IFN)-{gamma}] on transcriptional responses of bone marrow-derived macrophages (BMDM) to infection with Yersinia enterocolitica. IFN-{gamma} treatment more profoundly altered the transcriptome of BMDM than did bacterial infection or genetic background. In BALB/c BMDM, 1,161 genes were differentially expressed in response to Yersinia infection with or without IFN-{gamma} prestimulation. Fourteen genes (1.2%) could only be induced by BALB/c BMDM in response to Yersinia infection after IFN-{gamma} pretreatment. These genes inhibit apoptosis, activate NF-{kappa}B and Erk signaling, are chemotactic to neutrophils, and are involved in cytoskeletal reorganization, hence possibly in phagocytosis. Ten of these genes possess a common module of binding sites for Hox, Pou, and Creb transcription factors in 2 kb of upstream genomic sequence, suggesting a possible novel role of these transcription factors in regulation of immune responses. Fifty-two of one thousand fifty differentially expressed genes (4.9%) were induced more strongly by C57BL/6 BMDM in response to Yersinia infection than BALB/c BMDM. These genes activate NK cells, have antibacterial properties, or are involved in sensing chemokines and lipopolysaccharide (LPS). These data show that host resistance factors modulate a surprisingly small, but identifiable and functionally significant, portion of the macrophage transcriptome in response to Yersinia infection.

bacterial infection; host response; BALB/c; C57BL/6


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 GRANTS
 REFERENCES
 
DURING BACTERIAL INFECTIONS, the interplay between virulence factors of the pathogen and defense factors of the host determines whether the infection remains unapparent or results in clinical disease. Factors determining bacterial pathogenicity are often proteins acting as virulence factors. As one well-characterized example, Yersinia enterocolitica injects anti-host effector proteins (Yersinia outer proteins; Yops) into professional phagocytes via a type III protein secretion/translocation system (TTSS) (15, 16). Both the TTSS and Yops are encoded by a 70-kb virulence plasmid (pYV) that is common to all pathogenic Yersinia species. The six established effector proteins interfere with distinct signaling pathways resulting in paralysis of phagocyte function. YopP blocks the nuclear factor-{kappa}B (NF-{kappa}B) and mitogen-activated protein kinase (MAPK) pathways and thus inhibits the production of proinflammatory cytokines and adhesion molecules (45, 46). YopP also induces programmed cell death in macrophages (47, 49). YopE, YopT, and YopO interfere with the actin cytoskeleton dynamics of the host cell through modulating the GTPases Rac and Rho, resulting in disruption of the actin cytoskeleton and impaired phagocytosis (1, 2). YopH is a tyrosine phosphatase that dephosphorylates focal adhesion complex proteins like FAK and p130Cas (24). The function of YopM is enigmatic to date.

In contrast to these well-characterized bacterial virulence factors, much less is known about host factors determining resistance or susceptibility against bacterial infections. However, different inbred mouse strains differ remarkably in susceptibility against Yersinia infection, with 50% lethal doses (LD50) of resistant strains (e.g., C57BL/6) being 100- to 1,000-fold higher after intravenous (iv) infection compared with susceptible strains (e.g., BALB/c) (5, 25). This difference in susceptibility seems to be under multigenic control and is not linked to the murine major histocompatibility complex (MHC) locus H-2 (26). This locus encodes proteins that present antigen-derived peptides to T cells, and BALB/c MHC molecules present different peptides than C57BL/6 MHC molecules. Thus the differences in presented antigenic peptides are not responsible for differences in susceptibility.

An important role in the control of systemic Yersinia infection has been attributed to an early induction of interferon (IFN)-{gamma} (5) or interleukin (IL)-12 (7) in resistant C57BL/6 mice: intravenous administration of IFN-{gamma} to BALB/c mice induces resistance comparable with that of C57BL/6 mice, and administration of IFN-{gamma}-specific antibodies renders C57BL/6 mice susceptible (5). Similarly, systemic administration of IL-12 protects BALB/c mice against Y. enterocolitica challenge (7). However, how exactly this intricate cytokine network acts to mediate antibacterial resistance remains to be determined.

On the basis of these studies, it seems plausible that host factors critically influence the outcome of a host-pathogen encounter. Here, we determine the impact of 1) host genetic background (susceptible BALB/c vs. resistant C57BL/6) and 2) IFN-{gamma} (as one example of a resistance-inducing cytokine) on the transcriptional responses of bone marrow-derived macrophages (BMDM) to Y. enterocolitica infection.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 GRANTS
 REFERENCES
 
Experimental setup.
To identify the impact of host factors on the transcriptome of BMDM after Y. enterocolitica infection, high-density oligonucleotide arrays were hybridized with RNA derived from three distinct experiments: 1) BALB/c BMDM infected with Y. enterocolitica (mimicking a susceptible situation in vivo), 2) BALB/c BMDM prestimulated with IFN-{gamma} and infected with Y. enterocolitica (mimicking a resistant situation in vivo), and 3) C57BL/6 BMDM infected with Y. enterocolitica (mimicking a resistant situation in vivo). An additional set of arrays was prepared from C67BL/6 BMDM stimulated with IFN-{gamma} and infected with Y. enterocolitica. Notably, all experiments were performed from three to four independent RNA preparations from independent cultures of bone marrow cells (biological replicates). Thus we can define five parameters impacting the gene expression profiles obtained: presence or absence of IFN-{gamma}, presence or absence of bacteria, bacterial strain employed for infections in vitro [control strain WA(pTTS, pP60) or virulent strain WA(pYV)], genetic background of BMDM (BALB/c or C57BL/6), and experimental replicate (1 through 4).

Generation and infection of BMDM.
These studies have been reviewed and approved by the institutional review committee. BMDM were generated by standard procedures. Briefly, C57BL/6 and BALB/c mice (Charles River Laboratories) were killed by CO2 asphyxiation, and femurs were removed using aseptic technique. Bone marrow cells were isolated by flushing femurs with DMEM-10% FCS. All subsequent steps were performed in DMEM-10% FCS supplemented with 10% L cell-conditioned medium. Adherent cells were removed by overnight attachment to tissue culture plates. Nonadherent cells were differentiated into bone marrow macrophages for 8 days with a single media change at day 5. The resulting cell population was >90% M1/70 ({alpha}-CD11b) positive by fluorescence-activated cell sorting (FACS) (not shown).

Infection with Y. enterocolitica was performed essentially as described earlier (30). The following Yersinia strains were used (52). 1) Strain WA(pYV) is a serotype O:8 wild-type strain carrying the virulence plasmid and translocating all effector proteins (Yops) (29). 2) Strain WA(pTTS, pP60) is a derivative of WA(pYV) engineered in our lab (52), carrying the 25-kb fragment of the pYV plasmid coding for the TTSS on one plasmid (pTTS), plus a second plasmid encoding a translational fusion between amino acids 1 and 138 of Y. enterocolitica YopE with an inactive form of Listeria monocytogenes p60 murein hydrolase. This strain has been demonstrated to translocate an intracellularly inactive protein into the host cell (30) and thus serves as a control for Yop effects.

Stationary overnight bacterial cultures grown at 27°C were diluted 1:10 in fresh LB medium and incubated for 2 h at 37°C to induce expression of virulence factors. Macrophages were infected at a multiplicity of infection (MOI) of 50:1, and bacteria were spun onto the cell monolayer at 350 g for 5 min. Adherence of bacteria and translocation of Yops into the cytoplasm of host cells result in characteristic morphological changes (phagocytosis of bacteria, rounding and detachment of cells from the culture dish surface), and it was determined microscopically that this interaction took place in every experiment. After 60 min, gentamicin was added to a final concentration of 150 µg/ml, and RNA was isolated as indicated 3 h postinfection with TRIzol RNA isolation reagent.

RNA labeling, array hybridization, and statistical analysis.
Total cellular RNA was labeled and hybridized to Affymetrix MOE430A arrays (interrogating 22,690 transcripts) as recommended by the manufacturer. All experiments were performed in triplicate. Raw fluorescence intensity files were generated with Affymetrix MicroarraySuite v.5 software. Arrays were normalized, and model-based expression values were calculated, according to the methods of Li and Wong (34, 35). Differentially expressed genes were identified by the permutation-based method of Tusher et al. (53). Briefly, to control for multiple testing, a false discovery rate (FDR) (6) was calculated as the percentage of genes falsely detected as differentially expressed among all genes detected as differentially expressed. The q value is the lowest FDR at which the gene is called significant. Significant genes were identified at the most stringent q value possible. Cluster analysis of differentially expressed genes was performed according to Eisen et al. (19), using an uncentered Pearson correlation as similarity metric on z score-transformed gene expression values and average linkage clustering. Functional annotations were performed using Gene Ontology (4) as implemented in the NetAffx (36) database. Groups of coexpressed genes were tested for overrepresentation of functional categories using a hypergeometric distribution analysis. The entire list of differentially expressed genes is available as Supplemental Table S1 (available at the Physiological Genomics web site),1 and the gene expression values are available as Supplemental Table S2. The raw data are available at the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) under accession no. GSE2973.

Real-time RT-PCR.
For independent confirmation of gene expression results obtained with oligonucleotide microarrays, total cellular RNA was isolated at indicated time points postinfection as described above. RNA preparations for RT-PCR were independent from those used for array hybridizations. After random hexamer-primed first-strand cDNA synthesis (Superscript II, Invitrogen), real-time PCR was performed in an ABI PRISM 7000 Sequence Detection system (Applied Biosystems) using an initial denaturation at 95°C for 10 min followed by 40 cycles of 95°C for 15 s and 60°C for 1 min. Primers and fluorescent probes were designed using Primer3 software (http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi) or taken from the Mouse ProbeLibrary kit (Exiqon, Vedbaek, Denmark). Sequences or probe numbers are listed in Table 1. Gene expression levels were recorded relative to the HPRT housekeeping control as E = 2–{Delta}CT (where E = gene expression value and {Delta}CT = difference in crossing points between HPRT and genes) (30). All PCR experiments were performed from at least two independent experiments, and standard deviations from duplicate runs were calculated and displayed as error bars. For graphical display, the maximum gene expression value in every graph was given an arbitrary value of 10, and the remaining values and standard deviations were scaled accordingly, graphwise.


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  		Table 1. PCR primers and probes used in this study

 
Promoter analysis.
For analysis of conserved transcription factor-binding sites in promoters of coexpressed genes, 2 kb of genomic sequence upstream from the transcriptional start site were extracted from Ensembl (http://www.ensembl.org/). In cases where two or more alternatively spliced transcripts were linked to the same Affymetrix probe set identifier, the transcript with the most 5' transcriptional start site was used. Conserved transcription factor-binding sites and common frameworks were identified with MatInspector and FrameWorker software from Genomatix (Munich, Germany) (13).

Measurement of apoptosis.
Strain WA(pTTS, pYopP) (52) has been described. After infection at an MOI of 50:1, BMDM were detached from the culture dish surface by treatment with dispase II (Roche Applied Science) according to manufacturer's recommendations. Apoptosis was measured at 5 h with annexin V-FITC and propidium iodide (BD Biosciences Pharmingen) or FITC-VAD-FMK in situ marker (Promega) according to manufacturer's recommendations. Fluorescence intensities were quantified on a Coulter EpicsXL flow cytometer.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
GRANTS
 REFERENCES
 
Impact of experimental variables on the transcriptome of BMDM.
To identify which of our experimental parameters (presence or absence of IFN-{gamma}, presence or absence of bacteria, bacterial strain employed for infections in vitro, genetic background of BMDM, or experimental replicate) had the greatest impact on the transcriptome of BMDM, we performed an unsupervised hierarchical cluster analysis over the complete set of 22,690 genes from all 37 arrays employed in this study (Fig. 1). Presence or absence of IFN-{gamma} partitioned all samples into two distinct groups (dark red bar, without, and light red, with IFN-{gamma}). Within these two groups, presence of bacteria partitioned the samples into distinct groups (dark blue bars, without, and light blue, with bacterial infection). Within these groups, genetic background partitioned the samples into distinct groups (dark yellow bars, BALB/c, and light yellow, C57BL/6). Thus presence or absence of IFN-{gamma} has the highest impact on BMDM transcriptomes, followed by presence or absence of bacterial infection, followed by genetic background. The two bacterial strains employed [virulent strain WA(pYV) and control strain WA(pTTS, pP60)] could not be clearly distinguished, indicating that the transcriptional responses elicited by the two strains in BMDM are similar.


Figure 1
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  		Fig. 1. Tree diagram of a hierarchical cluster analysis of 37 arrays used in this study. Arrays were grouped according to gene expression levels of all 22,690 genes. Shorter branches indicate more similar gene expression profiles. Experimental parameters are represented by colored bars: red, interferon (IFN)-{gamma}; blue, bacteria; yellow, mouse strain. Bc, BALB/c; Bl6, C57BL/6; Mock, uninfected cells; p60, WA(pTTS, pP60); WAP, WA(pYV).

 
Transcriptional responses of BMDM to Y. enterocolitica infection.
Figure 2 shows a hierarchical cluster diagram of 597 genes that were detected as differentially expressed in C57BL/6 BMDM after infection with either WA(pTTS, pP60) or WA(pYV) at an FDR of 1.05% (see MATERIALS AND METHODS and legend to Fig. 2 for details of the graphical depiction). Four major groups of genes could be discerned in Fig. 2: groups A–D.


Figure 2
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  		Fig. 2. Hierarchical cluster diagram of 597 differentially expressed genes [false discovery rate (FDR) cutoff 1.05%] in C57BL/6 BMDM in response to Yersinia infection. Expression levels are color coded, with red indicating levels above, green below, and black near the mean gene expression value across all conditions. Groups of coexpressed genes are indicated by letters. Bacterial strains are indicated on top. The entire list of genes is available as Supplemental Material.

 
Group A [170 genes induced by infection with WA(pTTS, pP60) as well as by infection with WA(pYV)] is significantly enriched for immune response genes [P value for enrichment of Gene Ontology (GO) category "immune response" in group A from Fig. 2: <10–6] and genes involved in intercellular communication (P = 1.9 x 10–3), signal transduction (P = 2.19 x 10–4), and inhibition of apoptosis (P = 2.15 x 10–3). The fact that so many immune response genes were induced by both Yersinia strains is surprising, since we have shown earlier that in J774 macrophage-like cells, induction of such genes was inhibited by YopP of strain WA(pYV) (30). Thus BMDM macrophages were, on the transcriptional level, more resistant to action of YopP than J774 macrophage-like cells.

We hypothesized that, if BMDM are resistant to the action of YopP on gene transcription, this could translate into resistance against induction of apoptosis. Consistently, infection of BALB/c or C57BL/6 BMDM with strain WA(pTTS, pYopP), which translocates only YopP and induces apoptosis in J774 cells, does not result in increased annexin V staining compared with strain WA(pTTS, pP60) (Fig. 3). Similar results were obtained using a fluorescent marker for activated caspase 3 (FITC-VADFMK) or on comparing strain WA(pYV) with an isogenic YopP deletion strain WA(pYV{Delta}YopP) (data not shown). Thus YopP does not induce apoptosis in BMDM.


Figure 3
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  		Fig. 3. Apoptosis induced by Yersinia enterocolitica strains WA(pTTS, pP60) and WA(pTTS, pYopP). Left: in C57BL/6 bone marrow-derived macrophages (BMDM). Right: BALB/c BMDM. Cells were infected for 5 h at a multiplicity of infection (MOI) of 50:1 and stained with annexin V-FITC. Blue, mock-infected cells; green, cells infected with strain WA(pTTS, pYopP); red, cells infected with strain WA(pTTS, pP60). x-Axis: FITC fluorescence intensity, log scale. y-Axis: no. of events recorded.

 
The reasons for this resistance against YopP remain to be determined. It has recently been shown that signaling via Toll-like receptor (TLR)4 and Toll/IL-1 receptor domain-containing adaptor-inducing IFN-ß (TRIF) is necessary to induce apoptosis in macrophages (48). Thus TLR4 signaling via TRIF may not be fully functional in BMDM. Interestingly, studies with human cells show that ex vivo-isolated monocytes are also resistant against YopP-induced apoptosis, whereas monocyte-derived macrophages are susceptible (K. Ruckdeschel, personal communication). It might thus be that BMDM are more immature than J774 cells, and thus more resistant against apoptosis.

Interestingly, it seems that BALB/c BMDM are less susceptible to induction of apoptosis than are C57BL/6 BMDM (compare annexin V staining intensity between Fig. 3, left and right), irrespective of the bacterial strain. Consistently, the group of Yersinia-induced and pYV-resistant genes in C57BL/6 BMDM (group A in Fig. 2), but not the corresponding group in BALB/c BMDM, is significantly (P < 0.01) enriched for genes of GO categories "cell death" and "apoptosis." This may indicate that BALB/c BMDM are generally less responsive to bacterial stimuli than are C57BL/6 BMDM (see below) and thus exhibit a lower amount of apoptosis.

Group B in Fig. 2 contains a smaller number of genes (n = 40) whose induction in response to Yersinia infection could be inhibited by virulent strain WA(pYV). The functions of genes from group B are similar to those from group A, and several members of this group encode potentially important antimicrobial effectors. For example, myosin X is recruited to phagocytic cups and links phosphatidylinositol 3-kinase signaling to pseudopod extension during phagocytosis (17). Tnfrsf12a, also known as fn14 or tweakr, encodes a cell surface receptor that mediates proinflammatory effects [IL-8 and granulocyte/macrophage colony-stimulating factor (GM-CSF) production, upregulation of intercellular adhesion molecule (ICAM)-1 and E-selectin] in human epithelial and endothelial cells (27, 55). Bsf4 encodes a cytokine of the IL-6 family that has been shown to increase B cell numbers as well as IgG and IgM levels when administered in vivo (51).

Group C [4 genes induced by virulent strain WA(pYV) but not by control strain WA(pTTS, pP60)] contains genes of unknown functions. Group D in Fig. 2 (382 genes suppressed by either strain) contains genes involved in ribosome structure (P = 1.5 x 10–5), mitochondrial function (P = 1 x 10–6), regulation of transcription (P = 9.6 x 10–4), or metabolism (P = 1.4 x 10–3).

Thus Yersinia infection suppressed expression of genes with general cellular and metabolic functions and induced expression of immune response genes. The latter effect was only partially inhibited by action of Yops.

Although fewer genes could be detected as differentially expressed in BALB/c BMDM in response to Y. enterocolitica infection, the overall pattern of gene expression was similar to that in C57BL/6 macrophages (data not shown). The group of genes induced only by virulent strain WA(pYV) (group C in Fig. 2) in BALB/c BMDM (8 genes), however, contained several genes with known inactivating functions. klf4 inhibits expression of CD11d and thus efficiently inhibits neutrophil attachment and migration to sites of infection (41). vav3 overexpression perturbs cytokinesis and leads to the appearance of multinucleated cells (22). yy1 is a pleiotropic transcription factor that may inhibit IFN-ß signaling (54), suppresses the transactivation activity of Notch (56), and inhibits transcription from sterol-regulatory element-binding protein response genes (20). We thus suggest that translocation of Yops may inhibit immune responses in BMDM from susceptible BALB/c, but not from resistant C57BL/6, mice by induction of silencing genes. We have recently demonstrated a similar effect in BALB/c-derived J774 macrophages (30).

To independently confirm these array-based gene expression data, we performed real-time quantitative PCR (RT-qPCR) for representative genes from the most important groups in Fig. 2: two genes induced by the action of Yops (figf, spred2), one gene whose induction by strain WA(pTTS, pP60) can be inhibited by action of Yops (ilrn), and one gene whose induction by strain WA(pTTS,pP60) cannot be inhibited by the action of Yops (ccl9). As shown in Fig. 4, the overall expression pattern could be confirmed for every gene. There were, however, some minor differences in the extent of increase or decrease of mRNA levels between RT-qPCR and array data. Ilrn appeared slightly more suppressed by translocation of virulence proteins in the RT-qPCR assay than in the array data (Fig. 4C), and the array measured slightly higher baseline mRNA expression levels for ccl9 in C57BL/6 BMDM than the RT-qPCR (Fig. 4D). Because RNA samples for RT-qPCR were prepared independently from those used for array analysis, these differences may represent experimental variations.


Figure 4
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  		Fig. 4. Confirmation of array data by real-time quantitative PCR (RT-qPCR). Black bars represent RT-qPCR expression levels, whereas shaded or open bars indicate array-based gene expression levels. Affymetrix probe set identifiers are given at right of each; Human Genome Organisation (HUGO) gene symbols are at top. Expr. rel. to HPRT, expression relative to the HPRT housekeeping control. Error bars are 1 standard deviation from the mean of 2 (RT-qPCR) or 3 (array) experiments.

 
Ccl9 mRNA could be confirmed to be induced despite the action of Yops in both C57BL/6 (Fig. 4D) and BALB/c (Fig. 4E) BMDM. To exclude that this Yop resistance was a time-dependent effect, we performed a time course analysis of ccl9 expression in BALB/c and C57BL/6 BMDM up to 4 h postinfection. Figure 5 shows that Yops from strain WA(pYV) did not significantly inhibit ccl9 mRNA expression at any time point in BMDM from both genetic backgrounds. We cannot formally exclude, however, that other genes from group A in Fig. 2 behave differently.


Figure 5
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  		Fig. 5. Time course analysis of ccl9 mRNA expression in BALB/c (black bars) or C57BL/6 (open bars) BMDM. Graphical display as in Fig. 4.

 
Several earlier studies evaluated the impact of Yersinia infection on the transcriptome of immortalized epithelial (9) and macrophage (30, 50) cell lines. One of the major differences is the degree of Yop resistance of many proinflammatory genes. While in J774 macrophages, most immune response genes are suppressed by the action of Yops (30), PU5-1.8 macrophages are slightly more similar to BMDM, since almost twice as many genes are Yop resistant than are Yop susceptible in this cell line (50).

Impact of IFN-{gamma} on the transcriptional response of BALB/c BMDM to Y. enterocolitica infection.
Because BALB/c mice can be rendered resistant against Y. enterocolitica infection by systemic administration of IFN-{gamma}, we wondered how IFN-{gamma} would modify the transcriptional response of BALB/c BMDM to Yersinia infection. We thus treated BMDM from BALB/c mice with 50 U/ml IFN-{gamma} overnight, infected with Y. enterocolitica as described above, and compared gene expression patterns with those of cells not treated with IFN-{gamma}.

Figure 6 shows a hierarchical cluster diagram of 1,161 genes detected as differentially expressed with an FDR of 0.1%. Group A in Fig. 6 contains 312 genes whose expression was suppressed by IFN-{gamma} irrespective of bacterial infection. Vice versa, group F contains 301 genes whose expression was induced by IFN-{gamma} irrespective of bacterial infection. Groups B and D contain genes that were not affected by IFN-{gamma} and were either suppressed (group B, 341 genes) or induced (group D, 144 genes) in response to Y. enterocolitica infection. IFN-{gamma} inhibited Yersinia-elicited mRNA induction of 49 genes from group E.


Figure 6
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  		Fig. 6. Hierarchical cluster diagram of 1,161 differentially expressed genes (FDR cutoff, 0.1%) in BALB/c BMDM without (left) or after (right) overnight IFN-{gamma} pretreatment. Graphical display as in Fig. 2. Bottom: enlarged display of group C. The entire list of genes is available as Supplemental Material.

 
A number of genes with presumed inactivating functions (klf4, vav3, and yy1) are induced only by Yop-translocating Yersiniae in BALB/c BMDM (see above). It could be expected that IFN-{gamma} pretreatment would inhibit expression of these genes. In fact, IFN-{gamma} abolishes the ability of Yop-translocating strain WA(pYV) to induce vav3 and yy1, but not klf4, mRNA expression (not shown).

Group C contains 14 genes (1.2% of all genes from Fig. 6) that were induced in BALB/c BMDM in response to Y. enterocolitica infection only after IFN-{gamma} pretreatment (enlarged display in Fig. 6, bottom). Induction of some of these genes can be inhibited by Yops only in IFN-{gamma}-naive cells. Genes involved in inhibition of apoptosis (P = 0.01), chemotaxis (P = 0.0028), or cytoskeleton organization (P = 0.028) occurred significantly more often in group C than would be expected by chance.

Many of these genes induced in response to Yersinia infection only after IFN-{gamma} pretreatment qualify as mediators of Yersinia resistance in vivo. For example, both cflar (also known as flip or casper) and bcl2a1a (also known as A1) are antiapoptotic genes. Cflar also promotes activation of NF-{kappa}B and Erk signaling pathways (32) and thus may be involved in regulating other immune response genes. The chemotaxin G1p2 may attract neutrophils to the site of infection (43). Palm has been implicated in plasma membrane dynamics and cell process formation of neurons (33), so it may be involved in regulating macrophage migration or phagocytosis.

To evaluate whether there was a common regulatory mechanism underlying coordinated expression of these 14 genes, we analyzed 2 kb of upstream genomic sequence for occurrence of common transcription factor-binding sites. We could identify 12 unique promoters (2 probe sets aligned multiple times to the mouse genome sequence). These 12 promoters have a total of 50 transcription factor-binding sites in common (not shown). To restrict this large set of putatively involved transcription factors, we evaluated whether some of these binding sites would occur in characteristic patterns in the majority of the 12 promoter sequences. Ten of twelve (83%) promoters examined contained a module comprised of one binding site for homeodomain (HOX) transcription factors on the plus strand, followed by a POU- and a HOX-binding site on the minus strand, followed by a cAMP-responsive element-binding protein (CREB)-binding site on the plus strand (Fig. 7). The probability of obtaining 10 sequences containing this model when randomly drawing 12 sequences from a reference set of 5,000 human promoters is P = 4.7 x 10–12. Moreover, when analyzing a control set of genes with a related expression pattern, we find this model in only 18 of 65 (27%) promoters of genes that were inducible both by IFN-{gamma} and by Yersinia infection and whose expression patterns were at least as highly correlated as those of group C genes (a subgroup of group D in Fig. 6). We conclude that the occurrence of this transcription factor-binding site module in 10 of 12 promoters from a group of coexpressed genes is unlikely to occur by chance.


Figure 7
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  		Fig. 7. Promoter analysis of 10 transcripts regulated synergistically by IFN-{gamma} and Yersinia infection in BALB/c BMDM. ENSEMBL transcript IDs are indicated at left; 2 kb of promoter sequence are represented by dashed lines. Red marks indicate transcriptional start sites. Green, yellow, and blue marks indicate binding sites for Hox, Pou, and Creb transcription factors, respectively. Symbols above dashed lines indicate sites on the plus strand, symbols below on the minus strand.

 
If transcriptional regulation occurs via these transcription factor-binding sites, one would expect corresponding transcription factors to be expressed in Yersinia-infected and IFN-{gamma} stimulated BMDM. In fact, the arrays detected constitutive mRNA expression of nine transcription factors of the CREB family (atf-1 through -5, creb-1, creb-2, crem, and nfil3), one HOX transcription factor (chx-10), and one POU transcription factor (pou6f1) in all six RNA samples of IFN-{gamma}-stimulated and Yersinia-infected BMDM. Thus IFN-{gamma} prestimulation followed by Yersinia infection could potentially activate cooperative transcriptional activation by expressed HOX, POU, and CREB transcription factors, and future studies will test this hypothesis.

The occurrence of CREB factors in an immune response signature could be expected, since phosphorylation of CREB protein has been described as being mediated by numerous stimuli, like rise in intracellular cAMP or calcium concentration, growth factor signaling, or integrins (37). HOX and POU factors, in contrast, have not previously been associated with regulation of immune response genes. HOX genes are master regulators of developmental processes controlling the diversification of segments along the anteroposterior axis of animals (31). HOX genes have also been implicated in the development of solid organs, like kidney or prostate, indicating that they have at least one additional function beyond regulating homeosis (31). POU transcription factors also have important developmental functions, like inhibition or promotion of cell proliferation, determination of cell lineages, regulation of cell migration, survival, and terminal differentiation (3). Interestingly, interactions between CREB, POU, and HOX factors have been described. For example, HOX and POU factors have been shown to regulate expression of the paired homeodomain transcription factor pax3 (44), and the POU transcription factor Oct-1 potentiates CREB-driven expression of cyclin D1 (12).

An earlier study (18) investigated transcriptional responses of BMDM to IFN-{gamma} and Myobacterium tuberculosis. The authors found that IFN-{gamma} suppresses slightly more genes than it induces, a result that we can confirm [312 genes suppressed by IFN-{gamma} (group A in Fig. 6), 301 genes induced by IFN-{gamma} (group F in Fig. 6), ratio of suppressed to induced = 51:49]. These authors find substantial synergism between M. tuberculosis and IFN-{gamma}, in that the number of genes regulated in response to a combination of both stimuli greatly exceeds the number of genes regulated by either stimulus alone. In contrast, we can only identify a very small number of synergistically regulated genes (group C in Fig. 6). While this may partly be due to differences in microarray data analysis strategies, it may well reflect differences in infection biology and lifestyle (intra- vs. extracellular persistence) between M. tuberculosis and Y. enterocolitica. In fact, several earlier studies demonstrated that transcriptional responses to infection are pathogen specific to a certain extent (14, 40).

Impact of host genetic background on the transcriptional response to Y. enterocolitica infection.
To determine the impact of the genetic background of the host on transcriptional responses to Y. enterocolitica infection, we directly compared Yersinia-elicited gene expression patterns of BALB/c and C57BL/6 BMDM. Figure 8, top, shows a hierarchical cluster diagram of 1,050 genes detected as differentially expressed with an FDR cutoff of 0.25%. Genetic background had no effect on genes from group A (224 genes induced in both BALB/c and C57BL/6 BMDM after infection) or group D (576 genes suppressed in BMDM from both mouse strains). Groups C and E contain 89 and 109 genes, respectively, that were constitutively expressed in BMDM from either mouse strain but whose expression was unaffected by Yersinia infection. Group B (enlarged display at bottom of Fig. 8) contains 52 genes (4.9% of all genes from Fig. 8) that were induced specifically (group B1, 27 genes) or more strongly (group B2, 25 genes) in C57BL/6 BMDM in response to Yersinia infection compared with BALB/c BMDM. Interestingly, transcription of some of the genes from group B2 seemed pYV resistant in C57BL/6, but not in BALB/c, BMDM. Group B is highly enriched for defense response genes (P = 3 x 10–3) and cytokines (P = 2 x 10–3). However, promoter analysis did not reveal a highly specific model of transcription factor-binding sites as in the group of IFN-{gamma}- and Yersinia-induced genes.


Figure 8
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  		Fig. 8. Hierarchical cluster diagram of 1,050 differentially expressed genes (FDR cutoff 0.25%) after Yersinia infection of BALB/c (left) or C57BL/6 (right) BMDM. Graphical display as Fig. 2. Bottom: enlarged display of group B. The entire list of genes is available as Supplemental Material.

 
Several genes in group B qualify as mediators of increased antimicrobial resistance of C57BL/6 BMDM compared with BALB/c BMDM. Notably, IL-12 is a prominent inducer of IFN-{gamma} in vivo, and it has been shown that administration of IL-12 is protective to BALB/c mice (10). Slamf7 encodes a transmembrane protein involved in activation of natural killer (NK) cells (11). Thus C57BL/6 mice may more profoundly activate NK cells than BALB/c BMDM, and an earlier IFN-{gamma} induction by NK cells has been demonstrated in C57BL/6 mice compared with BALB/c (8). Ornithine decarboxylase (encoded by the odc1 gene), which is involved in polyamine biosynthesis and hence indirectly increases cell migration and proliferation, has been shown to participate in the control of Citrobacter rodentium colitis (23). The role of polyamines in the control of Yersinia infection has, however, not been investigated to date.

C57BL/6 BMDM also expressed higher levels of cell surface receptors [e.g., ccr3, the receptor for eotaxin, RANTES, MCP-2, MCP-3, and MCP-4 (28); ly78, a TLR-like protein regulating lipopolysaccharide (LPS) signaling in B cells (42)] and signaling molecules [pim1; ripk4, which activates NF-{kappa}B (39) and JNK (38); cdk5r1, which phosphorylates STAT3 and activates transcription of fos and jun (21)] than BALB/c BMDM. This suggests that C57BL/6 BMDM may be prone to responding more strongly to Yersinia infection than BALB/c BMDM. Consistently, we did not identify any genes that were induced in BALB/c BMDM in response to Yersinia infections to higher levels than in C57BL/6 BMDM.

Taken together, these data clearly show that the genetic background of the host has an identifiable and biologically meaningful impact on the gene expression of macrophages in response to bacterial infection. Future molecular and immunological studies will elucidate the impact of individual transcripts identified here on antimicrobial host responses.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 GRANTS
REFERENCES
 
This project was supported by the German Federal Ministry for Education and Research under the auspices of the National Genome Research Network, project nos. IE-S15T04 and NIE-S31T10.


   FOOTNOTES
 
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).

Address for reprint requests and other correspondence: R. Hoffmann, Max-von-Pettenkofer-Institut, Dept. Bacteriology, Pettenkoferstr. 9A, 80336 Munich, Germany (e-mail: r_hoffmann{at}mvp.uni-muenchen.de).

1 The Supplemental Material for this article (Supplemental Tables S1 and S2) is available online at http://physiolgenomics.physiology.org/cgi/content/full/00188.2005/DC1. Back


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  1. Aepfelbacher M and Heesemann J. Modulation of Rho GTPases and the actin cytoskeleton by Yersinia outer proteins (Yops). Int J Med Microbiol 291: 269–276, 2001.[CrossRef][Medline]
  2. Aepfelbacher M, Zumbihl R, Ruckdeschel K, Jacobi CA, Barz C, and Heesemann J. The tranquilizing injection of Yersinia proteins: a pathogen's strategy to resist host defense. Biol Chem 380: 795–802, 1999.[CrossRef][Medline]
  3. Andersen B and Rosenfeld MG. POU domain factors in the neuroendocrine system: lessons from developmental biology provide insights into human disease. Endocr Rev 22: 2–35, 2001.[Abstract/Free Full Text]
  4. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, and Sherlock G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25: 25–29, 2000.[CrossRef][ISI][Medline]
  5. Autenrieth IB, Beer M, Bohn E, Kaufmann SH, and Heesemann J. Immune responses to Yersinia enterocolitica in susceptible BALB/c and resistant C57BL/6 mice: an essential role for gamma interferon. Infect Immun 62: 2590–2599, 1994.[Abstract/Free Full Text]
  6. Benjamini Y and Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Stat Soc B 57: 289–300, 1995.
  7. Bohn E and Autenrieth IB. IL-12 is essential for resistance against Yersinia enterocolitica by triggering IFN-gamma production in NK cells and CD4+ T cells. J Immunol 156: 1458–1468, 1996.[Abstract]
  8. Bohn E, Heesemann J, Ehlers S, and Autenrieth IB. Early gamma interferon mRNA expression is associated with resistance of mice against Yersinia enterocolitica. Infect Immun 62: 3027–3032, 1994.[Abstract/Free Full Text]
  9. Bohn E, Muller S, Lauber J, Geffers R, Speer N, Spieth C, Krejci J, Manncke B, Buer J, Zell A, and Autenrieth IB. Gene expression patterns of epithelial cells modulated by pathogenicity factors of Yersinia enterocolitica. Cell Microbiol 6: 129–141, 2004.[CrossRef][ISI][Medline]
  10. Bohn E, Schmitt E, Bielfeldt C, Noll A, Schulte R, and Autenrieth IB. Ambiguous role of interleukin-12 in Yersinia enterocolitica infection in susceptible and resistant mouse strains. Infect Immun 66: 2213–2220, 1998.[Abstract/Free Full Text]
  11. Bouchon A, Cella M, Grierson HL, Cohen JI, and Colonna M. Activation of NK cell-mediated cytotoxicity by a SAP-independent receptor of the CD2 family. J Immunol 167: 5517–5521, 2001.[Abstract/Free Full Text]
  12. Boulon S, Dantonel JC, Binet V, Vie A, Blanchard JM, Hipskind RA, and Philips A. Oct-1 potentiates CREB-driven cyclin D1 promoter activation via a phospho-CREB- and CREB binding protein-independent mechanism. Mol Cell Biol 22: 7769–7779, 2002.[Abstract/Free Full Text]
  13. Cartharius K, Frech K, Grote K, Klocke B, Haltmeier M, Klingenhoff A, Frisch M, Bayerlein M, and Werner T. MatInspector and beyond: promoter analysis based on transcription factor binding sites. Bioinformatics 21: 2933–2942, 2005.[Abstract/Free Full Text]
  14. Chaussabel D, Semnani RT, McDowell MA, Sacks D, Sher A, and Nutman TB. Unique gene expression profiles of human macrophages and dendritic cells to phylogenetically distinct parasites. Blood 102: 672–681, 2003.[Abstract/Free Full Text]
  15. Cornelis GR. The Yersinia Ysc-Yop 'type III' weaponry. Nat Rev Mol Cell Biol 3: 742–752, 2002.[CrossRef][ISI][Medline]
  16. Cornelis GR, Boland A, Boyd AP, Geuijen C, Iriarte M, Neyt C, Sory MP, and Stainier I. The virulence plasmid of Yersinia, an antihost genome. Microbiol Mol Biol Rev 62: 1315–1352, 1998.[Abstract/Free Full Text]
  17. Cox D, Berg JS, Cammer M, Chinegwundoh JO, Dale BM, Cheney RE, and Greenberg S. Myosin X is a downstream effector of PI(3)K during phagocytosis. Nat Cell Biol 4: 469–477, 2002.[ISI][Medline]
  18. Ehrt S, Schnappinger D, Bekiranov S, Drenkow J, Shi S, Gingeras TR, Gaasterland T, Schoolnik G, and Nathan C. Reprogramming of the macrophage transcriptome in response to interferon-gamma and Mycobacterium tuberculosis: signaling roles of nitric oxide synthase-2 and phagocyte oxidase. J Exp Med 194: 1123–1140, 2001.[Abstract/Free Full Text]
  19. Eisen MB, Spellman PT, Brown PO, and Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 95: 14863–14868, 1998.[Abstract/Free Full Text]
  20. Ericsson J, Usheva A, and Edwards PA. YY1 is a negative regulator of transcription of three sterol regulatory element-binding protein-responsive genes. J Biol Chem 274: 14508–14513, 1999.[Abstract/Free Full Text]
  21. Fu AK, Fu WY, Ng AK, Chien WW, Ng YP, Wang JH, and Ip NY. Cyclin-dependent kinase 5 phosphorylates signal transducer and activator of transcription 3 and regulates its transcriptional activity. Proc Natl Acad Sci USA 101: 6728–6733, 2004.[Abstract/Free Full Text]
  22. Fujikawa K, Inoue Y, Sakai M, Koyama Y, Nishi S, Funada R, Alt FW, and Swat W. Vav3 is regulated during the cell cycle and effects cell division. Proc Natl Acad Sci USA 99: 4313–4318, 2002.[Abstract/Free Full Text]
  23. Gobert AP, Cheng Y, Akhtar M, Mersey BD, Blumberg DR, Cross RK, Chaturvedi R, Drachenberg CB, Boucher JL, Hacker A, Casero RA Jr, and Wilson KT. Protective role of arginase in a mouse model of colitis. J Immunol 173: 2109–2117, 2004.[Abstract/Free Full Text]
  24. Hamid N, Gustavsson A, Andersson K, McGee K, Persson C, Rudd CE, and Fallman M. YopH dephosphorylates Cas and Fyn-binding protein in macrophages. Microb Pathog 27: 231–242, 1999.[CrossRef][Medline]
  25. Hancock GE, Schaedler RW, and MacDonald TT. Yersinia enterocolitica infection in resistant and susceptible strains of mice. Infect Immun 53: 26–31, 1986.[Abstract/Free Full Text]
  26. Hancock GE, Schaedler RW, and MacDonald TT. Multigenic control of resistance to Yersinia enterocolitica in inbred strains of mice. Infect Immun 56: 532–533, 1988.[Abstract/Free Full Text]
  27. Harada N, Nakayama M, Nakano H, Fukuchi Y, Yagita H, and Okumura K. Pro-inflammatory effect of TWEAK/Fn14 interaction on human umbilical vein endothelial cells. Biochem Biophys Res Commun 299: 488–493, 2002.[CrossRef][ISI][Medline]
  28. Heath H, Qin S, Rao P, Wu L, LaRosa G, Kassam N, Ponath PD, and Mackay CR. Chemokine receptor usage by human eosinophils. The importance of CCR3 demonstrated using an antagonistic monoclonal antibody. J Clin Invest 99: 178–184, 1997.[ISI][Medline]
  29. Heesemann J and Laufs R. Construction of a mobilizable Yersinia enterocolitica virulence plasmid. J Bacteriol 155: 761–767, 1983.[Abstract/Free Full Text]
  30. Hoffmann R, Van Erp K, Trulzsch K, and Heesemann J. Transcriptional responses of murine macrophages to infection with Yersinia enterocolitica. Cell Microbiol 6: 377–390, 2004.[CrossRef][ISI][Medline]
  31. Hombria JC and Lovegrove B. Beyond homeosis—HOX function in morphogenesis and organogenesis. Differentiation 71: 461–476, 2003.[CrossRef][ISI][Medline]
  32. Kataoka T, Budd RC, Holler N, Thome M, Martinon F, Irmler M, Burns K, Hahne M, Kennedy N, Kovacsovics M, and Tschopp J. The caspase-8 inhibitor FLIP promotes activation of NF-kappaB and Erk signaling pathways. Curr Biol 10: 640–648, 2000.[CrossRef][ISI][Medline]
  33. Kutzleb C, Sanders G, Yamamoto R, Wang X, Lichte B, Petrasch-Parwez E, and Kilimann MW. Paralemmin, a prenyl-palmitoyl-anchored phosphoprotein abundant in neurons and implicated in plasma membrane dynamics and cell process formation. J Cell Biol 143: 795–813, 1998.[Abstract/Free Full Text]
  34. Li C and Wong WH. Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc Natl Acad Sci USA 98: 31–36, 2001.[Abstract/Free Full Text]
  35. Li C and Wong WH. Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol 2: research 0032.1–0032.11, 2001.
  36. Liu G, Loraine AE, Shigeta R, Cline M, Cheng J, Valmeekam V, Sun S, Kulp D, and Siani-Rose MA. NetAffx: Affymetrix probesets and annotations. Nucleic Acids Res 31: 82–86, 2003.[Abstract/Free Full Text]
  37. Mayr B and Montminy M. Transcriptional regulation by the phosphorylation-dependent factor CREB. Nat Rev Mol Cell Biol 2: 599–609, 2001.[CrossRef][ISI][Medline]
  38. Meylan E, Martinon F, Thome M, Gschwendt M, and Tschopp J. RIP4 (DIK/PKK), a novel member of the RIP kinase family, activates NF-kappa B and is processed during apoptosis. EMBO Rep 3: 1201–1208, 2002.[CrossRef][ISI][Medline]
  39. Muto A, Ruland J, McAllister-Lucas LM, Lucas PC, Yamaoka S, Chen FF, Lin A, Mak TW, Nunez G, and Inohara N. Protein kinase C-associated kinase (PKK) mediates Bcl10-independent NF-kappa B activation induced by phorbol ester. J Biol Chem 277: 31871–31876, 2002.[Abstract/Free Full Text]
  40. Nau GJ, Richmond JF, Schlesinger A, Jennings EG, Lander ES, and Young RA. Human macrophage activation programs induced by bacterial pathogens. Proc Natl Acad Sci USA 99: 1503–1508, 2002.[Abstract/Free Full Text]
  41. Noti JD, Johnson AK, and Dillon JD. The leukocyte integrin gene CD11d is repressed by gut-enriched Kruppel-like factor 4 in myeloid cells. J Biol Chem 2004.
  42. Ogata H, Su I, Miyake K, Nagai Y, Akashi S, Mecklenbrauker I, Rajewsky K, Kimoto M, and Tarakhovsky A. The toll-like receptor protein RP105 regulates lipopolysaccharide signaling in B cells. J Exp Med 192: 23–29, 2000.[Abstract/Free Full Text]
  43. Owhashi M, Taoka Y, Ishii K, Nakazawa S, Uemura H, and Kambara H. Identification of a ubiquitin family protein as a novel neutrophil chemotactic factor. Biochem Biophys Res Commun 309: 533–539, 2003.[CrossRef][ISI][Medline]
  44. Pruitt SC, Bussman A, Maslov AY, Natoli TA, and Heinaman R. Hox/Pbx and Brn binding sites mediate Pax3 expression in vitro and in vivo. Gene Expr Patterns 4: 671–685, 2004.[CrossRef][Medline]
  45. Ruckdeschel K, Harb S, Roggenkamp A, Hornef M, Zumbihl R, Kohler S, Heesemann J, and Rouot B. Yersinia enterocolitica impairs activation of transcription factor NF-kappaB: involvement in the induction of programmed cell death and in the suppression of the macrophage tumor necrosis factor alpha production. J Exp Med 187: 1069–1079, 1998.[Abstract/Free Full Text]
  46. Ruckdeschel K, Machold J, Roggenkamp A, Schubert S, Pierre J, Zumbihl R, Liautard JP, Heesemann J, and Rouot B. Yersinia enterocolitica promotes deactivation of macrophage mitogen-activated protein kinases extracellular signal-regulated kinase-1/2, p38, and c-Jun NH2-terminal kinase. Correlation with its inhibitory effect on tumor necrosis factor-alpha production. J Biol Chem 272: 15920–15927, 1997.[Abstract/Free Full Text]
  47. Ruckdeschel K, Mannel O, Richter K, Jacobi CA, Trulzsch K, Rouot B, and Heesemann J. Yersinia outer protein P of Yersinia enterocolitica simultaneously blocks the nuclear factor-kappa B pathway and exploits lipopolysaccharide signaling to trigger apoptosis in macrophages. J Immunol 166: 1823–1831, 2001.[Abstract/Free Full Text]
  48. Ruckdeschel K, Pfaffinger G, Haase R, Sing A, Weighardt H, Hacker G, Holzmann B, and Heesemann J. Signaling of apoptosis through TLRs critically involves toll/IL-1 receptor domain-containing adapter inducing IFN-beta, but not MyD88, in bacteria-infected murine macrophages. J Immunol 173: 3320–3328, 2004.[Abstract/Free Full Text]
  49. Ruckdeschel K, Roggenkamp A, Lafont V, Mangeat P, Heesemann J, and Rouot B. Interaction of Yersinia enterocolitica with macrophages leads to macrophage cell death through apoptosis. Infect Immun 65: 4813–4821, 1997.[Abstract]
  50. Sauvonnet N, Pradet-Balade B, Garcia-Sanz JA, and Cornelis GR. Regulation of mRNA expression in macrophages after Yersinia enterocolitica infection. Role of different Yop effectors. J Biol Chem 277: 25133–25142, 2002.[Abstract/Free Full Text]
  51. Senaldi G, Varnum BC, Sarmiento U, Starnes C, Lile J, Scully S, Guo J, Elliott G, McNinch J, Shaklee CL, Freeman D, Manu F, Simonet WS, Boone T, and Chang MS. Novel neurotrophin-1/B cell-stimulating factor-3: a cytokine of the IL-6 family. Proc Natl Acad Sci USA 96: 11458–11463, 1999.[Abstract/Free Full Text]
  52. Trulzsch K, Roggenkamp A, Aepfelbacher M, Wilharm G, Ruckdeschel K, and Heesemann J. Analysis of chaperone-dependent Yop secretion/translocation and effector function using a mini-virulence plasmid of Yersinia enterocolitica. Int J Med Microbiol 293: 167–177, 2003.[CrossRef][Medline]
  53. Tusher VG, Tibshirani R, and Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 98: 5116–5121, 2001.[Abstract/Free Full Text]
  54. Weill L, Shestakova E, and Bonnefoy E. Transcription factor YY1 binds to the murine beta interferon promoter and regulates its transcriptional capacity with a dual activator/repressor role. J Virol 77: 2903–2914, 2003.[Abstract/Free Full Text]
  55. Xu H, Okamoto A, Ichikawa J, Ando T, Tasaka K, Masuyama K, Ogawa H, Yagita H, Okumura K, and Nakao A. TWEAK/Fn14 interaction stimulates human bronchial epithelial cells to produce IL-8 and GM-CSF. Biochem Biophys Res Commun 318: 422–427, 2004.[CrossRef][Medline]
  56. Yeh TS, Lin YM, Hsieh RH, and Tseng MJ. Association of transcription factor YY1 with the high molecular weight Notch complex suppresses the transactivation activity of Notch. J Biol Chem 278: 41963–41969, 2003.[Abstract/Free Full Text]



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