Despite the essential role of dendritic cells in the priming of immune responses, the cellular and molecular mechanisms involved in regulating apoptosis and survival of dendritic cells are still poorly documented. Experimental data has suggested that activation of dendritic cells through either T cells or by engagement of pathogen-associated molecular patterns recognition suppresses dendritic cell apoptosis and promotes survival. In this study we investigated the mechanisms involved in regulating bone marrow derived dendritic cells (BMDCs) survival and apoptosis after cytidinephosphate-guanosine oligodeoxynucleotide (CpG-ODN) treatment. We found that addition CpG-ODN to BMDC cultures protected cells from spontaneous apoptosis; in addition, CpG-ODN also protected BMDCs from camptothecin-induced apoptosis. To identify transcription factors controlling CpG-ODN-mediated BMDCs survival we employed DNA microarrays, gene clustering and transcription element listening system (TELiS), a sequence-based bioinformatic tool that identifies transcription factor binding motifs that are over-represented among the promoters of upor down-regulated genes. Our analysis revealed that several transcription factors may play key roles in regulating CpG-ODN-induced BMDCs survival. Interestingly, the CCAAT/enhancer binding protein alpha (C/EBP ) was significantly over-represented among the promoters of the up-regulated genes; however its expression levels in nuclear extracts was significantly reduced following CpG-ODN treatment, suggesting that CpG-ODN-mediated survival of BMDCs is associated with decreased activation of C/EBP . In conclusion, our study suggested that in addition to NFB and AP-1, other transcription factors, such as C/EBP , also contribute to the regulation of CpG-ODN induced BMDC survival. INTRODUCTION Dendritic cells (DCs) are short lived, efficient professional antigen presenting cells (APCs), which bridge innate and adaptive immune responses . Immature DCs detect microbial infections through their pattern recognition receptors . Toll-Like Receptors (TLRs) represent a major group of these receptors that detect multiple pathogen associated molecular patterns (PAMPs), for example, TLR2 recognises bacterial lipoproteins and lipoteichoic acid, TLR4 detects LPS and major glycolipidic component of Gram-negative bacteria, whilst TLR9 recognizes unmethylated cytidinephosphate-guanosine DNA (CpG-DNA) of bacteria and viruses . Activation of DCs to efficient APCs for T cell priming can be initiated by engagement of TLRs. During activation DCs increase their ability to present and process antigens, up-regulate MHC class II and costimulatory molecules and produce several inflammatory cytokines . Experimental data also suggests that DC activation induced by engagement of PAMPs recognition promotes DC survival, for example, LPS and CpG oligodeoxynucleotide (CpGODN) have been demonstrated to inhibit cellular apoptosis *Address correspondence to this author at the Division of Mycobacterial Research, MRC National Institute for Medical Research, London, NW7 1AA, UK; Tel: 44 20 88162677; Fax: 44 20 88162564; E-mail: email@example.com [5-7]; in addition it has been shown that promotion of DC survival can promote specific immune responses [8, 9]. Thus, activation and regulation of DC survival are critical for mounting efficient innate immune responses to pathogens as well as for the development of effective T cell-mediated adaptive immune responses. Previously we demonstrated that activation of DCs by CpG-ODN promotes priming and activation of CD8 T cells . Despite the increasing knowledge in the mechanisms regulating priming of T cells by activated DCs [8-11], the cellular and molecular mechanisms involved in regulating activation and survival of DCs in response to CpG-ODN are still poorly documented, therefore, uncovering the molecular mechanisms regulating activation and survival of DCs would enhance our understanding of the intracellular pathways involved in promoting T cell priming. In addition, this information ultimately will be useful in developing DC-based immunotherapies and vaccines for diseases such as cancer and tuberculosis. It has been reported that CpG-ODN induced inhibition of spontaneous DC apoptosis by up-regulating cellular inhibitor of apoptosis proteins (cIAPS) . Sester and co-workers  demonstrated that CpG-ODN activated survival of murine macrophages through TLR9 and the phosphatidylinositol 3-kinase (PI3K)/Akt pathway. It is well characterised that CpG-ODN-induced DC maturation is regulated principally 68 The Open Immunology Journal, 2009, Volume 2 Yang et al. by the MyD88/IL-1-receptor-associated kinase (IRAK)/ TNF-receptor-associated factor (TRAF) signalling pathway ; however, signalling dependent on the DNA-dependent protein kinase (DNA-PK) has also been reported . Although the proximal events regulating signalling in DCs by CpG-ODN have been extensively studied, the global transcriptional responses involved in controlling activation and survival are less well characterised. In this study we demonstrate that treatment of bone marrow derived DC (BMDCs) with CpG-ODN results in the activation of BMDCs as well as prevention of apoptosis. We also characterise these responses using Affymetrix genome-wide DNA microarrays (mouse 430-2) combined with Transcription element listening system (TELiS)  to identify changes in gene expression and involvement of transcription factors that were over represented among the promoters of up-regulated genes. We have validated the expression levels of several important genes regulating cellular apoptosis and inflammatory response by real time PCR (RT-PCR) and examined the role of the CCAAT/enhancer binding protein alpha (C/EBP ) in controlling BMDC survival in response to CpG-ODN. MATERIALS AND METHODOLOGY Materials Camptothecin (CPT) was purchased from Sigma (Dorset, UK). Endotoxin-free phosphorothioate-stabilized CpG-ODN (GCATGACGTTGAGCT) and its control GpG-ODN (GCATGAGGTTGAGCT) were from Eurogentec (Seraing, Belgium). Anti-phospho-C/EBP was bought from Cell Signaling Technology (Beverly, MA). LY294002 was purchased from Superarray Bioscience (Frederick, MD). Cell permeable NFB inhibitor peptide, SN 50, and its control peptide, SN50M, were obtained from Calbiochem (Nottingham, UK). Cell Culture and Treatment BMDCs were extracted from C57BL/6 mice and cultured for 6 days in the presence of recombinant GM-CSF (R&D system, Minneapolis, MN). Cells were then purified using CD11c (N418) microbeads (Militenyi Biotech, Germany) and 92%-95% purity was achieved. On day 7, the BMDCs were stimulated with CpG-ODN or GpG-OND for 24 hrs. After 24 hrs conditioned medium was collected for cytokine measurement and the cells were processed for further experiments such as flow cytometry analysis and RNA isolation. Cytokine Measurements Sandwich ELISAs were used to measure the level of cytokines produced by cultured cells; these cytokines were IL1 , IL-6, IL-10, IL-12p40, TNF (e-Bioscience, Germany), IL-1 and IP-10 (R&D system). The sensitivity ranges of the ELISAs were: IL-1 (8pg/ml), IL-6 (4pg/ml), IL-10 (15pg/ml), IL-12p40 (8pg/ml), TNF (8pg/ml), IL-1 (10pg/ml) and IP-10 (30pg/ml). Apoptosis Detection BMDCs were harvested from the culture after appropriate treatment and washed twice in PBS. After blocking Fc receptors using anti-mouse CD16/CD32 (BD Bioscience Pharmingen, Oxford, UK) for 15 min at room temperature, the cells were stained with PI and annexin V (Annexin VFITC Apoptosis Detection Kit 1, BD Biosciences) for 45 min in dark at 4°C. Acquisition was performed on a FACScan (Becton Dickinson, Mountain View, CA). Data were analysed using WINMDI 2.6. Differential Expression of Gene Profile by DNA Microarray Analysis After BMDCs were treated with CpG-ODN for 24 hrs, total RNA was extracted using Trizol (Invitrogen, Paisley, UK). The quality of the RNA was checked using a Bioanalyser 2100 (Agilent Technologies, Santa Clara, CA). Microarray expression experiments (n=3) were performed using total RNA from three different sets of BMDC preparations. Briefly, 5μg of total RNA was used for one-cycle target labelling and hybridisation to the Affymetrix mouse genomeMOE430 2.0 array according to Affymetrix’s standard protocol (http://www.affymetrix.com). Labelled GeneChips were scanned and data files scaled to 100 prior to analysis with GeneSpring 7.3 software (Agilent Technologies). Genes were excluded if the signal strength did not significantly exceed background values and if expression did not reach a threshold value for reliable detection (based on the relaxed Affymetrix MAS 5.0 probability of detection (p 0.1)  in each of the three separate studies. Expression was median normalised per array and per gene, and genes were excluded if the level of expression did not vary by more than 1.4 fold between CpG-ODN treated compared with untreated control BMDCs. The remaining genes were subjected to nonparametric Welch tests and were reported with their respective fold changes and p-values. The functional enrichment analysis was performed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database that organises the genes (gene products) into pathway reaction maps  and can be used to illustrate causal relationships between genes (gene products). To predict which transcription factors control differential expression of a set of genes driven by CpG-ODN stimulation, the data of differentially expressed genes was then analysed using the TELiS database  which contains information on the prevalence of transcription factor binding motifs (TFBMs) in the promoters of mouse genes (24,384 genes). The results are organised as a ranked list of transcription factors which may control the gene expression caused by CpG-ODN. RT-PCR Analysis The same RNA samples used in the microarray study were analysed by RT-PCR. Equal amounts of RNA were used for cDNA synthesis using Superscript RT (Invitrogen) and RT-PCR products were detected using QuantiTect SYBR green PCR kit (Qiagen, Crawley, UK) and ABI prism 7000 (Applied Biosystems, Warrington, UK). Commercially available primers (Superarray Biosciences, USA) were used for the real-time PCR reactions. Controls for the real-time PCR reactions were performed using reverse transcriptase negative samples to exclude any DNA contamination. The test genes and normalizing gene were assayed along with a set of standard samples (genomic DNA). The expression value of individual genes was normalised to the 18sRNA house keeping gene and the transcript level of each gene was CpG Inhibits Bone Marrow Derived Dendritic Cell Apoptosis The Open Immunology Journal, 2009, Volume 2 69 expressed as an induction ratio of the sample with CpGODN treated relative to the untreated control. Detecting DNA-Protein Interactions Nuclear extracts were prepared from the BMDCs by using BD TM Transfactor Extraction Kit (BD Bioscience). Protein levels in nuclear extracts of BMDCs were measured using the Coomassie Protein Assay Regent Kit (Pierce, Rockford, IL). Protein levels of C/EBP and NFB in nuclear extracts were determined using BD Transfactor Kit (ELISA). Statistical Analysis Data are expressed as mean ± SD, unless otherwise stated. Comparisons between untreated control, CpG-ODN or GpG-ODN treated cultures were performed using Student's t-test for paired data. Values for p<0.05 were considered significant. RESULTS CpG-ODN Activates BMDCs and Protects Them from Apoptosis Addition of 10 μM CpG-ODN to BMDCs for 24 hrs resulted in elevated levels of IL-1 , IL-1 , IL-6, IL-10, IL12p40 and IP-10 in culture medium (Fig. 1) indicating BMDC activation. Consistent with our previously reported data , costimulatory molecules CD80 (B7-1) and CD86 (B7-2) were also found to be up-regulated in response to CpG-ODN by flow cytometer (data not shown). We then examined the effect of CpG-ODN on BMDC survival. BMDCs were cultured with CpG-ODN for 24 hrs, and cell apoptosis was examined using flow cytometry with annexin V and PI (Fig. 2A). The survival rate of BMDCs was significantly enhanced from 77.49% to 87.05% (p<0.003, Fig. 2B). This effect was not seen with GpGODN. In order to examine whether CpG-ODN can prevent drug-induced apoptosis of BMDCs, camptothecin (CPT), an anticancer drug that induces cellular apoptosis by inhibiting the activity of DNA topoisomerase-I  was added during the last 4 hrs of CpG-ODN or GpG-ODN treatment. As demonstrated in Fig. (2), treatment of BMDCs with CPT resulted in profound apoptosis within BMDCs, the survival of BMDCs decreasing from 77.497% to 14.59% (p<0.0001). However, CpG-ODN treatment protected BMDCs undergoing CPT-induced apoptosis, and cell survival returned to 50.84% from 14.59% (p<0.0001). The effect of CpG-ODN mediated protection of apoptosis was CpG motif specific since GpG-ODN showed no protection towards CPTinduced BMDCs apoptosis. Thus, our data showed that CpGODN protected BMDCs from both spontaneous and druginduced apoptosis. Transcriptomic Analysis of CpG-ODN Activated BMDCs To understand the molecular mechanisms regulating BMDCs activation and survival in response to CpG-ODN treatment, we employed Affymetrix DNA microarray analysis to obtain profiles of differentially expressed genes from BMDCs after treatment with 10 μM CpG-ODN for 24 hrs. Our microarray analysis revealed that 2039 out of 39000 genes were differently expressed after CpG-ODN treatment when a minimum 1.4 fold change in their expression levels was applied.
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