Dos Santos Mendes et al 2009 Cell Signal

Published in : Cellular Signalling (2009), vol 21, pp 1109-1122 Status : Postprint (Author’s version) Microarray analyses of the effects of NF-κB or PI3K pathway inhibitors on the LPS-induced gene expression profile in RAW264.7 cells Synergistic effects of rapamycin on LPS-induced MMP9-overexpression Sofia Dos Santos Mendes a, Aurélie Candi a, Martine Vansteenbrugge a, Marie-Rose Pignon b, Hidde Bult c, Karim Zouaoui Boudjeltia d, Carine Munaut b, Martine Raes a a University of Namur-FUNDP, Research Unit in Cellular Biology, Rue de Bruxelles, 61, B-5000 Namur, Belgium b Laboratory of Tumor and Development Biology, CRCE, CHU, GIGA, University of Liège, Sart Tilman B-4000, Liège, Belgium c Division of Pharmacology, University of Antwerp, 2610 Wilrijk, Belgium d Laboratoire de Médecine Expérimentale (ULB 222 Unit), ISPPC, CHU Charleroi - Hôpital André Vésale, Montigny-Le-Tilleul, Belgium ABSTRACT Lipopolysaccharide (LPS) activates a broad range of signalling pathways including mainly NF-κB and the MAPK cascade, but recent evidence suggests that LPS stimulation also activates the PI3K pathway To unravel the specific roles of both pathways in LPS signalling and gene expression profiling, we investigated the effects of different inhibitors of NF-κB (BAY 11-7082), PI3K (wortmannin and LY294002) but also of mTOR (rapamycin), a kinase acting downstream of PI3K/Akt, in LPS-stimulated RAW264.7 macrophages, analyzing their effects on the LPS-induced gene expression profile using a low density DNA microarray designed to monitor the expression of pro-inflammatory genes After statistical and hierarchical cluster analyses, we determined five clusters of genes differentially affected by the four inhibitors used In the fifth cluster corresponding to genes upregulated by LPS and mainly affected by BAY 11-7082, the gene encoding MMP9 displayed a particular expression profile, since rapamycin drastically enhanced the LPS-induced upregulation at both the mRNA and protein levels Rapamycin also enhanced the LPS-induced NF-κB transactivation as determined by a reporter assay, phosphorylation of the p38 and Erk1/2 MAPKs, and counteracted PPAR activity These results suggest that mTOR could negatively regulate the effects of LPS on the NF-κB and MAPK pathways We also performed real-time RT-PCR assays on mmp9 expression using rosiglitazone (agonist of PPARγ), PD98059 (inhibitor of Erk 1/2) and SB203580 (inhibitor of p38MAPK), that were able to counteract the rapamycin mediated overexpression of mmp9 in response to LPS Our results suggest a new pathway involving mTOR for regulating specifically mmp9 in LPS-stimulated RAW264.7 cells Keywords : LPS ; Microarray ; NF-KB ; Rapamycin ; MMP9 Introduction Lipopolysaccharide (LPS), a major component of the outer membrane of Gram negative bacteria, activates intracellular signalling pathways of a remarkable complexity in monocytes-macrophages, leading these cells to a pro-inflammatory state, with the secretion of cytokines and overexpression of several markers of the immune response [1] LPS first binds to LBP (LPS-binding protein) and CD14, before docking to the receptor complex built up by TLR4 (Toll-like receptor 4) and MD-2 Signal is transduced via different sets of adaptor proteins: Mal (MyD88 adaptor-like protein also known as TIRAP or TIR-domain adaptor protein) and MyD88 (myeloid differentiation factor 88) control the MyD88 dependent pathway leading mainly to the expression of proinflammatory cytokines while TRAM (TRIF-related adaptor molecule) and TR1F (TlR-containing adaptor molecule) control the MyD88 independent pathway leading to the expression of the interferon and interferoninducible genes (for a recent review see [2]) Both pathways lead to the activation of protein kinases such as IRAK and (IL-1R activated kinases and 4), the adaptor protein TRAF6 (tumor necrosis factor (TNF)receptor-associated factor 6) and TAK1 (transforming growth factor-β-activated kinase 1) for the MyD88 dependent pathway, and RIP-1 (receptor-interacting protein 1) and TRAF3 (tumor necrosis factor (TNF)receptor-associated factor 3) for the MyD88 independent pathway These kinases activate the IKK and MAPK [2-4] Published in : Cellular Signalling (2009), vol 21, pp 1109-1122 Status : Postprint (Author’s version) NF-κB is a pivotal transcription factor in the orchestration of the inflammatory response initiated by LPS In normal conditions, NF-κB forms a dimeric complex, most frequently the canonical p65-p50 dimer, bound to its inhibitor, mainly IκBα Upon activation, IκBα is rapidly phosphorylated by the IKK complex and ubiquitinylated, then degraded by the 26S proteasome, exposing the NLS (nuclear localisation sequence) of NFκB The active dimer translocates to the nucleus where it induces the expression of pro-inflammatory genes like the cytokines IL-1β, TNF-α, IL-6 and MCP-1 (see reference [5] for a review) Transactivation of NF-κB is regulated at different levels Phosphorylation of p65 in response to many stimuli like IL-1, TNF-α or LPS, favours the recruitment of p300/CBP, optimizing the NF-κB response It also promotes p65 acetylation which in turn increases NF-κB transcriptional activity [6] Activity of NF-κB is also controlled by nuclear receptors (NR), and particularly PPARγ for which ligand dependent transrepression has been reported for NF-κB, but also for AP-1 [7] If NF-κB is a central actor in the response to LPS, less is known about the possible role of the PI3K (phosphoinositide-3 kinase)/Akt pathway and of mTOR, a kinase downstream of Akt, in LPS signalling Upon activation, PI3K is translocated to the plasma membrane where it phosphorylates phosphoinositides on three potential free hydroxyl groups of the inositol ring, producing phosphatidylinositol-3,4,5-triphosphate (PIP 3) A plethora of effector proteins are recruited at the plasma membrane because of their ability to associate with phosphoinositides via PH (pleckstrin homology) domains [8-10], PDK1 (phosphoinositide-dependent kinase 1) and Akt/PKB (protein kinase B), both Ser/Thr kinases, are central key players in the PI3K pathway that are recruited to the plasma membrane where phosphorylation on Thr308 of Akt by PDK1 is facilitated, stimulating the catalytic activity of Akt The latter is fully activated by phosphorylation on Ser473 by mTORC2 (mTOR complex 2) The mammalian target of rapamycin (mTOR), another Ser/Thr kinase, exists in two functionally distinct complexes called mTORC1 and mTORC2 mTORC1, composed of mTOR, mLST8/GβL (G protein βsubunit like protein) and raptor (regulatory associated protein of mTOR) is sensitive to rapamycin, unlike mTORC2 which is composed of mTOR, mLST8/GβL and rictor [11,12] Rapamycin binds to the cytosolic FK binding protein 12 (FKBP12), forming a complex targeting mTORC1, inhibiting mTOR kinase activity Activation of mTOR is mediated by Akt, that phosphorylates the tuberous sclerosis complex-2 (TSC-2) tumor suppressor gene product tuberin, inhibiting the tuberin-hamartin complex (also known as TSC-1-TSC-2 complex) [13,14] TSC2, a GTPase activating protein, favours the GTPasic activity of Rheb (Ras homology enriched in brain) converting Rheb-GTP into Rheb-GDP, unable to activate mTORC1 [15] Thus Akt, by inhibiting TSC2, activates Rheb and subsequently mTOR Substrates of mTOR include the inhibitory eIF4Ebinding proteins (4E-BPs) and the ribosomal kinase S6K Activated mTOR promotes translation by phosphorylating 4E-BPs relieving their binding to eIF4E, mediating interaction of eIF4F with the 5' cap structure of mRNAs S6K is activated by phosphorylation on Thr389 by mTOR, and can in turn phosphorylate the ribosomal protein S6, which is a critical determinant in the control of cell size [16-19], There is some evidence of the possible involvement of the PI3K/Akt/ mTOR pathway in LPS activation, based mainly on the use of inhibitors of this pathway, however, with conflicting results Park et al [20] showed that wortmannin, an inhibitor of PI3K, enhanced LPS-induced iNOS expression both at the mRNA and protein levels, and subsequent NO production in murine peritoneal macrophages However according to Weinstein et al [21], PI3K and mTOR mediate LPS-stimulated NO production, since LY294002 or rapamycin inhibits this production in RAW264.7 macrophages Finally Pahan et al [22] using rat C6 glial cells observed that iNOS upregulation by LPS could be achieved only in the presence of wortmannin or LY294002 (both PI3K inhibitors) Clearly the role of the PI3K/Akt/mTOR pathway in LPS activation is far of being elucidated in particular in monocytes/macrophages, one of the important cell targets of LPS Concerning mTOR, conflicting results have also been reported in the literature If various studies have suggested pro-inflammatory roles for mTOR [23,24], other authors suggest anti-inflammatory properties of mTOR in LPS-induced inflammatory cellular responses [25,26] To better characterize the involvement of mTOR in LPS signalling, in parallel to NF-κB and the PI3K/Akt pathway, we have investigated the various effects of rapamycin, the inhibitor of mTOR [27] in parallel with known inhibitors of the PI3K/Akt pathway (wortmannin [28] and LY294002 [29]) and with a well-described inhibitor of NF-κB (BAY 11-7082 [30]) on the gene expression profile of LPS-stimulated murine RAW264.7 macrophages We identified five clusters of genes which were differentially affected by these inhibitors, suggesting concomitant different regulatory pathways of gene expression Finally, we highlighted a novel role for mTOR, in the negative regulation of mmp9 (or gelatinase B) in LPS-stimulated RAW264.7 macrophages, as LPS and rapamycin synergize to favour its overexpression Published in : Cellular Signalling (2009), vol 21, pp 1109-1122 Status : Postprint (Author’s version) Materials and methods 2.1 Reagents LPS and rapamycin were purchased from Sigma, BAY 11-7082 and LY294002 from Calbiochem, and wortmannin from Biomol RAW264.7 cells were purchased from the ATCC 2.2 Cell culture The murine macrophage cell line RAW264.7 was cultured in DMEM (enriched with 4500 mg/l of glucose) (Gibco) containing 10% heat-inactivated fetal calf serum Cells were pre-incubated with BAY 11-7082 (12 µM), LY294002 (25 µM), wortmannin (1 µM) or rapamycin (1 µM) h before stimulation with LPS (100 ng/ml) in DMEM containing 1% of heat-inactivated serum 2.3 RNA extraction Total RNA was extracted from treated cells using the RNAgents Total RNA isolation System Kit (Promega) according to the manufacturer's protocol To assess the RNA integrity and concentration, samples were analyzed by capillarity electrophoresis on the Agilent 2100 BioAnalyzer (Agilent Technologies) RNA was extracted from three independent cultures for each condition 2.4 Reverse transcription Reverse transcription with indirect labelling (through the incorporation of biotin-dNTP during cDNA synthesis) was performed according to the DualChip® instruction manual (starting material: 15 µg of total RNA), as previously described in details [31], 2.5 Hybridization The hybridization on the array DualChip® mouse inflammation (Eppendorf) was carried out according to the DualChip® instruction manual The hybridization reaction was performed overnight (16 h) at 60 °C in a Thermoblock for DC (DualChip®) Slides used with a Thermomixer comfort (Eppendorf) 2.6 Detection and data analysis Detection and quantification of the hybridization events were carried out using a confocal laser scanner (ScanArray® 4000XL (PerkinElmer Life Sciences)) The ImaGene® 5.5 software (BioDiscovery®) was used for signal quantification Using the DualChip® evaluation software, the fluorescence intensity for each DNA spot was calculated using local mean background subtraction Normalization was performed in two steps, first via the internal standards present on the array (six different genes allowing quantification/normalization and estimation of experimental variation) and secondly using a set of House Keeping Genes The variance for the normalized set of housekeeping genes was used to generate a confidence interval to test the significance of the gene expression ratios obtained (condition tested versus control) [31,32] Ratios outside the 95% confidence interval were determined to be significantly different Ratios were then analyzed using the MeV 4.0 free software (http://www.tm4.org/mev.html) We first performed a one-way Analysis of Variance (ANOVA), followed by Hierarchical Clustering analysis (HCL) on significant data 2.7 Real-time RT-PCR Reverse transcription was performed using Oligo(dT) primers and Superscript™ III reverse transcriptase (Invitrogen Life Sciences) according to the manufacturer's recommendations Murine TBP, PAK1, MAPK14, NOS2, SERPINE1, IL-10, MCP-1, BCL-3, PML, NFκB1 (p50) and MMP9 were amplified using the following primer sets: TBP (forward, 5'-CAG TTA CAG GTG GCA GCA TGA-3' and reverse, 5'-TAG TGC TGC AGG GTG ATΓ TCA G-3'); PAK1 (forward, 5'-AAG GTG CTT CAG GCA CAG TGT A-3' and reverse, 5'-TCG GCT GCT GCT GAA GAT T-3'); MAPK14 (forward, 5'-CCGTGG GCT GCA TCA TG-3' and reverse, 5'-TTC CAA CGA GTC TTA AAA TGA GCT-3'); N0S2 (forward, 5'-CCT GGT ACG GGC ATT GCT-3' and reverse, 5'-CGG Published in : Cellular Signalling (2009), vol 21, pp 1109-1122 Status : Postprint (Author’s version) CAC CCA AAC ACC AA-3'); SER-PINE1 (forward, 5'-GGC ATG CCT GAC ATG TTT AGT G-3' and reverse, 5'-CGT TTA CCT CGA TCC TGA CCT T-3'); IL-10 (forward, 5'-AGT TCA GAG CTC CTA AGA GAG TTG TGA-3' and reverse, 5'-CCT CTG AGC TGC TGC AGG AA-3'); MCP-1 (forward, 5'-TCT GGG CCT GCT GTT CAC A-3' and reverse, 5'-CCT ACT CATTGG GAT CAT CTT GCT-3') ; BCL3 (forward, 5'-CAT CGA TGC AGT GGA TAT CAA GA-3' and reverse, 5'-CGA GCT GCC AGA ATA CAT CTG A-3') ; PML (forward, 5'-CAG CAC GCC TGA GGA CCT T-3' and reverse, 5'-TCT TGA TGA TCT TCC TGG AGC AA-3'); NFκB1/p50 (forward, 5'-CAG TAC CAC CTA TGA TGG GAC TAC AC-3'and reverse, 5'CAA GAG TCG TCC AGG TCA TAG AGA-3') and MMP9 (forward, 5'-TGG TGT GCC CTG GAA CTC A-3' and reverse, 5'-TGG AAA CTC ACA CGC CAG AAG-3') RT products (5 µg) were amplified in 25 àl containing the Power SYBRđ Green PCR Master Mix (Applied Biosystems) according to the manufacturer's protocol, using the ABI 7900HT (Applied Biosystems) 2.8 Zymography RAW264.7 cells were stimulated with LPS (10 ng/ml) in the absence or the presence of rapamycin at different concentrations, in serum-free medium during 24 h Conditioned media were collected and separated by SDSPAGE in 10% polyacrylamide gels containing 0.1% gelatine under non-reducing conditions Gels were then washed in renaturing buffer (2% Triton X-100) for × 30 min, and times with distilled water They were incubated overnight in the incubation buffer (50 mM Tris HCl, 10 mM CaCl2, pH 7.6), washed two times with distilled water, and then stained with Coomassie brilliant blue R-250 for 10-20 and destained with 20% methanol and 10% acetic acid 2.9 Macrophage transfection and luciferase assay The reporter plasmids pNF-κB-Luc and pAP1-Luc containing multiple copies of the NF-κB and API consensus DNA sequences were purchased from Stratagen and Clontech, respectively The luciferase construct driven by a synthetic promoter containing three PPAR responsive element (PPRE) sites (tk-PPREx3-Luc) was obtained from the lab of Prof R M Evans (Howard Hughes Medical Institute, The Salk Institute for Biological Studies) Transfections were performed using Lipofectamine 2000 from Invitrogen µg of DNA and µl of Lipofectamine 2000 were separately mixed to 100 µl OptiMEM After min, the Lipofectamine 2000 mixture was added to the DNA mixture and incubated at room temperature for 20 before being added to the cells seeded at 250,000 cells/well in a 12-well plate, containing ml of high glucose DMEM enriched with 10% inactivated serum After 24 h, cells were rinsed and stimulated or not in 1% serum containing medium for 24 h Cells were then washed twice with PBS and lysed with 150 µl Glo lysis buffer (Invitrogen) before assaying the luciferase activity, using the Bright-Glo™ luciferase assay system (Promega) Data were normalized by calculating the ratios of luciferase activity per mg of proteins determined by the Bradford method 2.10 Western blot analysis After being washed in PBS, cells were lysed in lysis buffer (10 mM TRIS, 100 mM NaCl, 10% glycerol, 1% NP40, 0.1% SDS, 0.5% deoxycholate, pH 7.4) containing the protease inhibitor cocktail obtained from Roche, Inc Equal amounts of total proteins were separated by SDS-PAGE on 10% polyacrylamide gels and transferred to a PVDF membrane before immunoblotting with primary anti phospho-p44/p42 MAPK (Cell Signalling), phospho-p38 MAPK (Cell Signalling) or α-tubulin antibodies (Sigma) Membranes were then treated with goat anti-rabbit IgG or goat anti-mouse IgG antibodies coupled to horseradish peroxidase (Amersham Pharmacia Biotech), revealed using the enhanced chemiluminescence detection kit (ECL advance - Amersham) and exposed to a X-ray film Published in : Cellular Signalling (2009), vol 21, pp 1109-1122 Status : Postprint (Author’s version) Table Description of the genes included in the five clusters Gene symbol Cluster CX3CR1 Gene name Chemokine (C-X3-C) receptor FOS FBJ osteosarcoma oncogene MAP3K1 Mitogen activated protein kinase kinase kinase MAPK14 Mitogen activated protein kinase 14 PAK1 p21 (CDKN1A)-activated kinase Cluster MYC Myelocytomatosis oncogene NOS2 Nitric oxide synthase 2, inducible, macrophage SERPINE1 Serine (or cysteine) proteinase inhibitor, clade E, member Cluster IL13RA2 Interleukin 13 receptor, alpha Fold induction (ratios) LPS + inhibitor LPS BAY LY294002 11-7082 Mean SD Mean SD Mean SD Wortmannin Rapamycin Aliases Genbank Gene function ∕ NM_009987 0.16 0.06 0.24 0.02 0.38c 0.11 0.21 0.01 0.15 0.05 c-fos MAPKKK1, Mekk, MEKK1 p38 alpha MAP Kinase NM_010234 NM_011945 0.40 0.46 0.09 0.09 0.37 0.41 0.05 0.56 0.11 0.55 0.10 0.47 0.11 0.53 0.15 0.10 0.39 0.44 0.15 0.14 0.38 0.10 0.48 0.17 0.83c 0.26 0.56 0.05 0.46 0.10 PAK-1, Paka NM_011035 0.49 0.08 0.49 0.04 0.96c 0.26 0.51 0.07 0.47 0.10 c-myc iNOS NM_010849 NM_010927 Receptor for the chemokine fractalkine Transcription factor Protein kinase, Ser/Thr (non-receptor) Protein kinase, Ser/Thr (non-receptor) Protein kinase, Ser/Thr (non-receptor) Transcription factor Oxidoreductase activity PAI-1 NM_008871 5.31 CD213a2 NM_008356 73.23 10.84 3.72c 1.33 15.47c 5.46 60.38 6.83 46.85a 9.28 NM_011951 ++ ++ + + 1.99 1.72b 0.49 9.13b 1.81 ++ + 2.21a IL15 Interleukin 15 / NM_008357 CSF2 Gm-CSf NM_009969 IL-1ra NM_031167 MCP1, monocyte chemoattractant protein-1 MCP-3 NM_011333 NM_013654 C-C chemokine activity +++ + ++ +++ +++ IL10 Colony stimulating factor (granulocyte-macrophage) Interleukin receptor antagonist Chemokine (C-C motif) ligand Chemokine (C-C motif) ligand Interleukin 10 NM_010548 + ++ +++ +++ Interleukin +++ + ++ +++ IRF7 MAP3K8 Interferon regulatory factor Mitogen activated protein kinase kinase kinase Interleukin receptor, alpha / Cot/Tp12 NM_016850 NM_007746 Cytokine - inflammatory response Cytokine - inflammatory response Transcription factor Ser/Thr kinase - NF-κB activation Receptor for the cytokine IL4 +++ IL6 Cytokine synthesis inhibitory factor, II-10 IL-6 13.60 8.55 3.79 0.66 4.85 CCL2 CCL7 IL4RA NM_031168 CD124, IL-4 receptor alpha NM_010557 chain 4.77 ++ ++ Mean SD Plasminogen activator inhibitor - prothrombotic Receptor for the cytokine IL13 Cytokine-cytokine receptor interaction Secreted proteins -hematopoeitins Cytokine - immune response C-C chemokine activity IL1RN 0.75 + + Mean SD + + - + + ++ + + ++ ++ +++ + ++ +++ +++ +++ + ++ +++ +++ 0.29 0.50 0.62a 0.02 5.58 1.11b 0.03 1.90a +++ + 2.54 21.65 12.65 10.68 0.29 5.95b 1.80 3.24 5.70 0.56 1.34b 0.31 2.05b 0.33 9.47c 2.57 0.33 2.3 2a Published in : Cellular Signalling (2009), vol 21, pp 1109-1122 Status : Postprint (Author’s version) MX1 Myxovirus (influenza virus) resistance Mx, Mx-1, myxovirus (influenza) resistance polypeptide IL-1a NM_010846 Protein binding - immune response + + + ++ + IL1A Interleukin alpha NM_010554 TIMP-1 NM_011593 +++ ++ ++ + Tissue inhibitor of metalloproteinase Beta-2 microglobulin +++ + + +++ ++ ++ +++ ++ ++ Ly-m11 NM_009735 c-maf S74567 PML Avian musculoaponeurotic fibrosarcoma (v-maf) AS42 oncogene homolog Promyelocytic leukemia Cytokine - inflammatory response Inhibitor of metalloproteinase MHC class I receptor activity Transcription factor TIMP1 Trim19 NM_008884 SAA1 IL10RA Serum amyloid A1 Interleukin 10 receptor, alpha Saa-1 mIL-10R NM_009117 NM_008348 TGFB1 TGF-beta CD80 IL18 Transforming growth factor, beta fos-like antigen Mitogen activated protein kinase kinase Interleukin receptor, gamma chain Signal transducer and activator of transcription CD80 antigen Interleukin 18 JAK2 - 1.72 0.72 0.95a 0.07 1.40 0.39 2.23 0.27 1.79 0.20 5.47 4.50 0.89a 0.27 1.40 0.63 8.35 4.45 2.64 1.19 2.68 0.80 0.85b 0.20 1.73 0.69 3.75a 0.47 2.02 0.58 ++ 1.75 0.43 + + 0.80a 0.48 2.10 ++ 0.49 2.21 ++ 0.40 2.28 0.64 NM_011577 Zinc ion binding regulation of transcription Lipid transporter activity Receptor for the cytokine IL10 Growth factor and cytokine 1.89 0.34 0.94a 0.36 2.06 0.85 2.09 0.21 2.15 0.65 Fra-2 MAP kinase kinase 1, MEK1, MEKK1 CD132, common cytokine receptor gamma chain / NM_008037 NM_008927 Transcription factor Protein kinase (MAPK) 3.72 1.83 0.13 0.24 1.46c 0.44 2.30a 0.98b 0.36 1.50 0.92 4.15 0.25 2.24 0.58 2.85 0.29 1.53 0.57 0.10 NM_013563 Cell surface receptor 1.65 0.27 0.78b 0.15 1.10a 0.25 1.92 0.18 1.83 0.28 NM_009283 Transcription factor 2.47 0.73 0.37b 0.14 1.70 0.86 3.25 0.79 2.43 0.71 Cd281, Ly-53 Igif, IL-18 NM_009855 NM_008360 ++ 4.45 0.67 + ++ 0.51c 0.04 2.65a ++ 0.59 6.72b ++ 0.23 5.81 0.55 Janus kinase / NM_008413 3.78 1.28 1.28a 0.65 3.88 1.64 5.71a 0.33 6.51b 1.08 BCL3 B-cell leukemia/lymphoma Bcl-3 NM_033601 7.46 1.84 1.56c 1.05 4.28a 1.52 10.16a 1.53 6.29 1.89 TNFAIP3 Tumor necrosis factor, alphainduced protein Chemokine (C-C motif) ligand Colony stimulating factor (granulocyte) Nuclear factor of kappa light chain gene enhancer in B-cells inhibitor, alpha Chemokine (C-C motif) ligand Zinc finger protein A20 NM_009397 TLR signalling Cytokine-cytokine receptor interaction Protein kinase, tyrosine (non-receptor) Cytoplasmic sequestering of NF-kappaB Ubiquitin-editing enzyme 18.69 2.55 0.97c 0.81 10.39b 2.64 23.50 3.69 16.83 3.61 MuRantes NM_013653 C-C chemokine activity +++ ++ +++ +++ +++ G-CSF NM_009971 +++ ++ +++ +++ +++ I(Kappa)B(alpha) NM_010907 Secreted proteins - cell proliferation Inhibitor of NF-κB MIP-1 alpha NM_011337 C-C chemokine activity ++ Cluster B2M MAF FOSL2 MAP2K1 IL2RG STAT1 Cluster CCL5 CSF3 NFκBIa CCL3 8.01 1.74 2.50b 0.57 7.02 ++ ++ 2.12 8.24 ++ 3.46 8.38 ++ 2.26 Published in : Cellular Signalling (2009), vol 21, pp 1109-1122 Status : Postprint (Author’s version) PTGS2 PDGF-B TNF TNFRSF1 B MMP9 IL1B TNFRSF5 NFκB1 TNFRSF6 TRAF1 Prostaglandin-endoperoxide COX2, cyclooxygenase synthase Platelet derived growth factor, PDGF-B, Sis B polypeptide Tumor necrosis factor TNF alpha, Tnfsf1a, tumor necrosis factor-alpha Tumor necrosis factor receptor CD120b, p75 TNFR, TNF superfamily, member b receptor beta chain, TNF-RII Matrix metalloproteinase 92 kDa gelatinase, 92kDa type IV collagenase, gelatinase B Interleukin beta IL-1beta Tumor necrosis factor receptor superfamily, member Nuclear factor of kappa light chain gene enhancer in B-cells 1, p105 Fas antigen NM_011198 NM_011057 NM_013693 +++ ++ +++ +++ +++ ++ + + ++ ++ 15.97 11.15 4.04a 2.64 16.42 6.36 10.71 3.73 19.84 9.61 ++ + ++ ++ ++ NM_013599 Protease (non-proteasomal) + + + ++ ++ +++ NM_008361 Cytokine - inflammatory response Cytokine signalling +++ + +++ +++ +++ 18.77 5.70 0.97c 0.26 15.09 3.35 24.91 4.25 24.95 2.75 NF-kappaB1, p50 subunit of NM_008689 NF-kappaB, p50/pl05 Transcription regulator 4.72 1.11c 0.51 4.61 1.27 5.18 1.22 4.45 0.93 CD95, Fas, APO-1 Death receptor family -apoptosis Adaptor in signal transduction - apoptosis ++ Cd40 TNF receptor-associated factor ∕ NM_011610 Prostaglandin and leukotriene metabolism Cell proliferation - MAPK signalling Cytokine - inflammatory response Tumor necrosis factor receptor activity NM_011611 NM_007987 NM_009421 5.47 0.82 + 2.26 +++ 1.62a 0.86 11.57b +++ 2.27 5.27 +++ 1.58 8.01 2.12 The GenBank™ accession number, common name and function of the genes (according to http://www.signaling-gateway.org/molecule/search) are provided For all the genes with quantitative ratios (see text for explanation), mean values of ratios of test versus control set arbitrarily to and standard deviations (SD) are provided Statistical analysis was performed by an ANOVA1 and the Holm-Sidak method Differences between the different "LPS + inhibitor" conditions in comparison with LPS alone were considered statistically significant at P