The JI
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     
 

The Journal of Immunology, 2008, 180, 8342 -8353
Copyright © 2008 by The American Association of Immunologists, Inc.
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Data Supplement
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ishmael, F. T.
Right arrow Articles by Stellato, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ishmael, F. T.
Right arrow Articles by Stellato, C.

Role of the RNA-Binding Protein Tristetraprolin in Glucocorticoid-Mediated Gene Regulation1

Faoud T. Ishmael*, Xi Fang*, Maria Rosaria Galdiero*, Ulus Atasoy{ddagger}, William F. C. Rigby{dagger}, Myriam Gorospe§, Chris Cheadle* and Cristiana Stellato2,*

* Division of Allergy and Clinical Immunology, Johns Hopkins University, Baltimore, MD 21224; {dagger} Dartmouth Medical School, Lebanon, NH 03755; {ddagger} Department of Surgery and Department of Molecular Microbiology and Immunology, University of Missouri, Columbia, MO 65212; and § Laboratory of Cellular and Molecular Biology, National Institute of Aging, National Institutes of Health, Baltimore, MD 21224


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
 References
 
Glucocorticoids (GCs) are the mainstay of anti-inflammatory therapy. Modulation of posttranscriptional regulation (PTR) of gene expression by GCs is a relevant yet poorly characterized mechanism of their action. The RNA-binding protein tristetraprolin (TTP) plays a central role in PTR by binding to AU-rich elements in the 3'-untranslated region of proinflammatory transcripts and accelerating their decay. We found that GCs induce TTP expression in primary and immortalized human bronchial epithelial cells. To investigate the importance of PTR and the role of TTP in GC function, we compared the effect of GC treatment on genome-wide gene expression using mouse embryonic fibroblasts (MEFs) obtained from wild-type and TTP–/– mice. We confirmed that GCs induce TTP in MEFs and observed in TTP–/– MEFs a striking loss of up to 85% of GC-mediated gene expression. Gene regulation by TNF-{alpha} was similarly affected, as was the antagonistic effect of GC on TNF-{alpha}-induced response. Inflammatory genes, including cytokines and chemokines, were among the genes whose sensitivity to GCs was affected by lack of TTP. Silencing of TTP in WT MEFs by small interfering RNA confirmed loss of GC response in selected targets. Immunoprecipitation of ribonucleoprotein complexes revealed binding of TTP to several validated transcripts. Changes in the rate of transcript degradation studied by actinomycin D were documented for only a subset of transcripts bound to TTP. These results reveal a strong and previously unrecognized contribution of PTR to the anti-inflammatory action of GCs and point at TTP as a key factor mediating this process through a complex mechanism of action.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Disclosures
 References
 
Glucocorticoids (GCs)3 are potent anti-inflammatory steroids that are used in treatment of the majority of inflammatory diseases (1, 2). The mechanism of their action is complex, and involves interference with many regulatory components of gene expression, from early actions on signal transduction pathways to late effects on posttranslational modifications (3, 4). GCs are well-known inhibitors of key proinflammatory genes such as TNF-{alpha}, GM-CSF, many ILs, and chemokines (4). Besides the powerful inhibition of the adaptive immune response, GCs also promote the innate arm of immunity by inducing genes functioning as anti- inflammatory factors, or preserving the expression of mediators of the innate immune responses (5, 6).

The regulation of gene transcription by GCs is a key feature of their anti-inflammatory action. Binding of GCs to the cytosolic GC receptor (GR) results in translocation of the ligand-activated GR to the nucleus, where it dimerizes and acts as a transcription factor, exerting effects on transcription through both DNA-dependent and -independent mechanisms (7, 8).

Mounting evidence indicates that GCs can regulate gene expression also altering posttranscriptional events (3). Transcriptional control is in fact highly integrated with the multiple steps of posttranscriptional regulation, which modulates the rates of mRNA transport, decay, and translation and crucially influences the timing and magnitude of cellular responses (9, 10). Phosphorylation-dependent stabilization of early response gene mRNAs, chiefly mediated by the MAPK p38, ERK, and the stress-activated protein kinase/JNK allows the achievement of a rapid rise in steady state levels and translation of cytokines and other key mediators in response to changes in cellular environment. This action is counterbalanced by pathways promoting mRNA decay to limit the amplitude and the duration of the response (11, 12). Regulation of mRNA turnover is well-recognized as a central means of controlling the inflammatory response (13, 14). Changes of mRNA stability can lead to rapid degradation of mRNA species and cessation of an inflammatory signal, or conversely, to the continued production of inflammatory genes through stabilization of their transcript and subsequent persistence of its inflammatory activity.

The adenylate/uridylate-rich elements (AREs) present within the 3'-untranslated region (UTR) of mRNAs represent the most characterized and well-conserved group of sequences functionally associated with the regulation of mRNA stability and translation (15, 16). Several in vivo and in vitro evidence indicate that the posttranscriptional control of inflammatory transcripts is strongly dependent on ARE-mediated mechanisms (9, 11, 17), highlighting the pathophysiological relevance to this pathway (14, 17, 18, 19).

Numerous ARE-binding proteins have been cloned and characterized as regulatory factors of mRNA decay and translation (20). The product of the ZFP-36 gene tristetraprolin (TTP), also known as TIS11, Nup475, and GOS24, is an RNA-binding protein (RBP) and member of a family of CCCH zinc finger proteins that include TTP, butyrate-response factor-1 and -2 (21). TTP promotes mRNA decay through binding of its zinc finger domain to an ARE consisting in adjacent UUAU/UUAU half-sites (22, 23, 24). It is induced as an immediate early response gene by inflammatory mediators, phorbol esters, LPS, and growth factors in a number of cell types, including T cells, macrophages, and fibroblasts where it displays a predominantly cytoplasmic localization (25). TTP has been shown to limit inflammation through a negative feedback loop on TNF-{alpha}-mediated activity, as TNF-{alpha} induces TTP synthesis, which in turn leads to destabilization of TNF-{alpha} mRNA (26). Moreover, TTP also mediates the mRNA decay of GM-CSF, cyclooxygenase-2, IL-2, IL-3, and inducible NO synthase (INOS) (27, 28, 29, 30, 31). Additional transcripts whose decay is regulated by TTP have been identified in a recent genome-wide study of mouse embryonic fibroblasts (MEFs) isolated from TTP-knockout (KO; TTP–/–) mice (32), and in mouse macrophages in which TTP expression was silenced (33). The importance of TTP in limiting the inflammatory response has been convincingly demonstrated in TTP–/– mice, which develop severe inflammatory arthritis, autoimmune dysfunction, and myeloid hyperplasia through the deregulated expression of TNF-{alpha} and GM-CSF (34).

Given the importance of posttranscriptional regulation in modulating the inflammatory response and the central role of GCs as anti-inflammatory agents, the question of whether TTP is involved in GC function arises. GCs have been shown to accelerate the mRNA decay of a number of cytokines, chemokines, and other proinflammatory molecules, but the molecular mechanisms by which GCs act on posttranscriptional events are still poorly understood (3). Smoak and Cidlowski (35) have recently demonstrated that GCs induce the production of TTP in vivo in several organs in mice, as well as in vitro in the airway A549 human epithelial cell line. Induction of TTP was transcriptionally regulated by GCs and was essential for GC-mediated inhibition of TNF-{alpha} through its ARE-bearing 3'-UTR.

Airway epithelium is a central player in the pathogenesis of airway allergic diseases such as asthma and a key target of inhaled GCs, the main therapeutic tool for inflammatory diseases (36). Several mediators of GC actions are induced in these cells, such as glucocorticoid-induced leucine zipper (37) and MAPK phosphatase-1 (38). In the present study, we show that GCs induce TTP expression in human primary bronchial epithelial cells (PBEC) and in the bronchial epithelial cell line BEAS-2B. To investigate the importance of TTP in GC function, we then examined by gene array analysis the global gene expression profile in wild-type (WT) and TTP–/– MEFs treated with the potent GC budesonide. We confirmed that GCs induce TTP expression also in our experimental system and report that GC-mediated gene expression is severely blunted in the absence of TTP. Antagonism of TNF-{alpha}-induced gene expression by GCs is also significantly diminished in TTP–/– MEFs. The loss of GC-induced gene repression was reproduced for selected validated genes in WT MEFs in which TTP expression was silenced with specific small interfering RNA (siRNA) treatment. Investigation into the mechanism of TTP action showed the association of TTP with a number of endogenous, ARE-bearing transcripts. However, lack of association of TTP with other validated genes points at the existence of concomitant complex indirect effects of TTP in GC-mediated action. Furthermore, the acceleration of mRNA decay of TTP-bound mRNA in response to GCs was reverted in TTP–/– cells only for a subset of transcripts, suggesting a regulatory role for TTP not limited to mRNA turnover.

Overall, our data implicate TTP as an important protein in the function of GCs, supporting its regulatory function on gene expression through complex mechanisms of action, and clearly indicate that posttranscriptional regulation is a major mechanism of the anti-inflammatory action of GCs.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Disclosures
 References
 
Cell culture and experimental protocols

PBECs were isolated by pronase digestion from bronchi of cadaveric lungs, as described (39). PBECs were cultured on collagen-coated flasks and maintained in serum-free LHC-9 medium (Biofluids). The BEAS-2B cell line, derived from human tracheal epithelium transformed by an adenovirus 12-SV40 hybrid virus (40), was supplied by Dr. C. Harris (National Institutes of Health, Bethesda, MD) and was maintained in F12/DMEM (Invitrogen Life Technologies), containing 5% heat-inactivated FCS, 2 mM L-glutamine, 100 U/ml penicillin, and 100 mg/ml streptomycin (Invitrogen). Littermate WT and TTP–/– E14.5 embryos were used to generate MEF cell lines 67+/+ and 66–/–, respectively (provided by Dr. P. J. Blackshear, National Institute of Environmental Health Sciences, Research Triangle Park, NC). Cells were grown as a monolayer in DMEM (Invitrogen) containing 10% FBS, 2 mM L-glutamine (Invitrogen), 100 U/ml each of penicillin and streptomycin (hereafter referred to as complete DMEM). TTP–/– cells were supplemented with 0.3 g/L geneticin (selection antibiotic; Invitrogen) every five passages as described (32). Once grown at 70% confluence, cells were cultured for 24 h before treatment in the same medium, but supplemented instead with 10% of a charcoal-stripped FBS (steroid-depleted; HyClone).

Budesonide was dissolved in the diluent DMSO (Sigma-Aldrich) to make a 0.1 M stock solution. To study the effect of budesonide on TTP expression, cell cultures (n = 3) were treated for 24 h with an equal volume of DMSO, budesonide (10–7 M) or TNF-{alpha} (10 ng/ml) for 1, 2, 6, or 24 h. TTP–/– MEFs treated with 10–7 M budesonide for 2 h served as a negative control. Cells were harvested by trypsinization and whole-cell lysates were isolated for protein analysis by Western blot as described (41).

For the gene expression study using Illumina arrays, cells (n = 3) were treated with an equal volume of DMSO or budesonide (10–7 M) for 3 h. DMSO- and budesonide-treated cells were left unstimulated or challenged with TNF-{alpha} for 1 additional hour prior the end of the incubation.

To study the rate of decay for selected targets, WT or TTP–/– MEFs were grown to 80% confluence and stimulated with budesonide (10–7 M) or DMSO for 3 h. Cells were then either harvested as control (time 0) or further cultured in the presence of the transcriptional inhibitor actinomycin D (Act D) (3 µg/ml). Total RNA was then isolated at various time points and the amount of remaining mRNA over control was quantified using real-time PCR, as described below.

RNA isolation and analysis of gene expression

Total RNA was extracted using the TRIzol reagent method (Invitrogen) and further purified using RNAeasy columns (Qiagen). The quality of total RNA samples was assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies).

For the array analysis, RNA samples (n = 3) were labeled according to the protocols recommended by the Illumina chip manufacturers. In brief, 0.5 µg of total RNA from each sample was labeled by using the Illumina TotalPrep RNA Amplification kit (Ambion). ssRNA (cRNA) was generated and labeled by incorporating biotin-16-UTP (catalog no. 11388908910; Roche Diagnostics); 0.85 µg of biotin-labeled cRNA was hybridized (for 16 h) to Illumina’s Sentrix MouseRef-8 Expression BeadChips (catalog no. BD-26-201; Illumina). The hybridized biotinylated cRNA was detected with streptavidin-Cy3 and quantitated using Illumina’s BeadStation 500GX Genetic Analysis Systems scanner. Multivariate correlations comparing each data set for each condition showed correlations with an r2 = 0.99 or above, with the only exception of one DMSO-treated data set in WT cells, which was excluded from the analysis due to a r2 = 0.93 in correlation with the other two sets for this condition.

Target validation for genes identified by array and by TTP-specific immunoprecipitation (IP; see below) was performed by real-time PCR using TaqMan probe and primers sets (Applied Biosystems). All samples were run in triplicate for real-time PCR fluorometric determination in an ABI 7700 sequence detector (PerkinElmer) and quantified using the comparative cycle threshold (CT) method (42, 43).

Analysis of protein levels

Protein concentration of whole-cell lysates was determined using a micro-BCA assay kit (Pierce). Protein samples (40 µg of total protein/sample) were subjected to SDS-PAGE separation and Western blot analysis as described (44, 45). A rabbit polyclonal anti-TTP Ab (CARM3) was used at a 1/5000 dilution (starting concentration of 0.9 mg/ml) to detect TTP, while expression of the GR was tested using rabbit polyclonal anti-GR Ab (Santa Cruz Biotechnology) at a 1/500 dilution. Anti-rabbit IgG linked to HRP (Amersham Biosciences) was used as a secondary Ab at a 1/5000 dilution. Following chemiluminescent development, the membranes were then probed with a 1/1000 dilution of β-tubulin (Santa Cruz Biotechnology) as a loading control. Densitometry of immunoreactive bands was performed on a Bio-Rad ChemiDoc XRS instrument. Bands were quantified as adjusted OD units per square millimeter and normalized to the β-tubulin signal.

Analysis of array data

Initial analysis of the scanned data was performed using Illumina BeadStudio software. The primary Illumina data are returned from the scanner in the form of an ".idat" file which contains single intensity data values/gene following the computation of a trimmed mean average for each probe type as measured by a variable number of bead probes/gene on the array. The Bead Studio software returns information on the number and SD of all the bead measurements per probe/gene as well as a detection call based on a comparison between the measured intensity calculated for a single probe/gene and the intensities measured for a large number of negative control beads built-in to the BeadChip arrays (D = percent above negative/100, 1 = perfect, i.e., the intensity value of a gene is greater than all the intensities for every negative control tested). Any gene consistently below D = 0.98 for all samples was eliminated from further analysis.

Raw intensity data for each experiment is log 10 transformed and then used for the calculation of Z scores (46). Z scores are calculated by subtracting the overall average gene intensity (within a single experiment) from the raw intensity data for each gene, and dividing that result by the SD of all the measured intensities, according to the formula: Z score = (intensityG1 – mean intensity G1... Gn)/SD G1... Gn, where G is any gene on the microarray and G1... Gn represents the aggregate measure of all the genes.

Calculation of significant changes in gene expression, which maximizes the power of replicates and takes into account variation between replicates on a gene by gene basis, is the two-sample-for-means Z test (47). The formula for this statistical test is as follows:

Formula
where (G1) represents the average Z score for any particular gene being tested under multiple experimental conditions (in this case, experimental vs control). The mean difference is corrected by the SE for the difference between means where {sigma}2 is the SD of repeated hybridization intensity measurements (expressed as Z scores) for either condition 1 or 2, and n equals the number of repeated measurements for either condition 1 or 2. Values of p can be assigned to the calculated Z test value by consulting the critical Z value for a two-tailed test in a standard normal distribution table. The lists of significant genes described (see Fig. 3, Tables I–III, supplemental files S1 to S3)4 were calculated by selecting genes which satisfied a significance threshold criteria of Z test p ≤ 0.001, a false discovery rate ≤0.1 (46), and a fold change ±2.0 or greater.


View this table:
[in this window]
[in a new window]

  		Table I. Loss of GC-induced gene down-regulation in TTP–/– MEFs compared to WT cellsa

 

View this table:
[in this window]
[in a new window]

  		Table II. Loss of GC-induced gene up-regulation in TTP–/– MEFs compared to WT cellsa

 

View this table:
[in this window]
[in a new window]

  		Table III. Loss of TNF-{alpha}-induced responses in TTP–/– MEFs compared to WT cellsa

 
Gene ontology (GO) analysis

Characterization of several observed gene clusters (see Table IV) was performed using the PANTHER software tool (www.pantherdb.org). This classification system groups genes based on function, using published scientific evidence and evolutionary relationships (47).


View this table:
[in this window]
[in a new window]

  		Table IV. GO of GC-regulated, TTP-dependent genes

 
IP of TTP-bound mRNAs

IP of RNP complexes (RNP-IP) was performed as described previously (41, 48). Briefly, 100 µl of preswelled protein A sepharose beads (Sigma-Aldrich) were washed with 1 ml of NT-2 buffer (50 mM Tris (pH 7.4), 150 mM NaCl, 1 mM MgCl2, 0.5% Nonidet P-40) and mixed with 10 µg of anti-TTP Ab or 10 µg of rabbit IgG (isotype control; BD Pharmingen). MEFs were cultured and as described above. Equal number of viable MEFs (10 x 106) treated with budesonide for 3 h were lysed in polysome lysis buffer (100 mM KCl, 5 mM MgCl2, 10 mM HEPES (pH 7.0), 0.5% Nonidet P-40, 1 mM DTT, 100 U/ml RNaseOUT (Invitrogen)), 0.2% vanadyl-ribonucleoside complex (Invitrogen), 0.2 mM PMSF, 1 mg/ml pepstatin A, 5 mg/ml bestatin, and 20 mg/ml leupeptin). The TTP- and control Ab-coated beads were then resuspended in 900 µl of the above buffer supplemented with 100 U/ml RNaseOUT, 0.2% vanadyl-ribonucleoside complex, 1 mM DTT, and 20 mM EDTA, then incubated (2 h at RT) with 100 µl of the messenger ribonucleoprotein (mRNP) cell lysate (30 mg/ml protein content). Washed beads were then incubated (30 min at 55°C) in buffer supplemented with 0.1% SDS and 30 µg of proteinase K. An aliquot of the immunoprecipitant (10 µg) was analyzed by Western blot, and RNA was extracted from the remaining sample using phenol/chloroform (Ambion).

RNA interference (RNAi) assay

WT MEFs were grown to 40% confluence. Complete DMEM was replaced with serum and antibiotics-free DMEM and cells were transiently transfected with TTP Stealth Select RNAi, MSS238871 (SiRNA1), or MSS238872 (SiRNA2; Invitrogen), or with negative control (Sc, Stealth RNAi Negative Control Med GC; Invitrogen) at a final concentration of 24 nM using Lipofectamine RNAiMAX reagent (Invitrogen) per the manufacturer’s instructions. After 6 h, the medium was replaced with complete DMEM, and the cells were brought to 80% confluence by a 36-h incubation. Cells were then stimulated with budesonide or DMSO, and protein and RNA were isolated as described (n = 4).

Statistical analysis

Statistical analysis for experiments besides the arrays (see Figs. 1 and 4–7) was performed using the Microsoft Excel software. Significance values (p ≤ 0.05) were determined by a two-tailed Student t test of treatment condition relative to control. Error bars on graphs represent the SEM.


Figure 1
View larger version (23K):
[in this window]
[in a new window]

  		FIGURE 1. Induction of TTP by budesonide in human airway epithelial cells and MEFs. Western blot analysis of TTP and β-tubulin (β-tub) levels in whole-cell extracts of PBEC and BEAS-2B cells (A) and WT MEFs (B) treated with DMSO, budesonide (Bud, 10–7 M), or TNF-{alpha} (10 ng/ml) for the indicated times. Mean ± SEM of n = 3. *, p < 0.05; **, p < 0.003 (relative to DMSO control). C, Levels of TTP in whole-cell extracts of WT and TTP–/– MEFs treated with budesonide (10–7 M) for 2 h, confirming that TTP is not expressed in the TTP–/– MEFs. D, Expression of the GR and β-tubulin by Western blot in WT and TTP–/– MEFs (representative of n = 3).

 

   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Disclosures
 References
 
GCs induce the synthesis of TTP in human airway epithelial cells and MEFs

Airway epithelial cells, either PBEC or BEAS-2B, were treated with budesonide (10–7 M) at different time points or with TNF-{alpha} (10 ng/ml) for 2 h as a positive control, or with the GC diluent DMSO as unstimulated control at the beginning and at the end of the kinetic experiments. Western blot analysis showed significant up-regulation of TTP following GC treatment. On average, TTP levels increased between 2.5 and 3.5 over the control in airway epithelial cells (Fig. 1A). In MEFs, TTP levels increased ~3-fold upon stimulation with budesonide from a low baseline signal (Fig. 1B), which remained unchanged between the two data points assessed (data not shown). Densitometric analysis of the Western blots revealed that expression of TTP was statistically significant between 1 and 6 h for both budesonide- and TNF-{alpha}-treated cells, with TTP levels remaining significantly elevated at 24 h only in the BEAS-2B cell line. Immunoreactive TTP appeared as multiple bands and/or as broad band, secondary to phosphorylation as observed previously (49). As expected, TNF-{alpha}-stimulated cells induced TTP in epithelial cells and in WT MEFs, while TTP was undetectable in the TTP–/– MEFs (Fig. 1C). To assess the reliability of the response to GCs in our experimental mouse model, we confirmed that the levels of the GR were comparable in the two cell types (Fig. 1D).

GC-mediated gene regulation is highly dependent on TTP in MEFs

To investigate the role of TTP in the mechanism of action of GCs, we set up a genome-wide analysis of GC-mediated gene expression in MEFs cell lines developed from TTP KO mice in comparison to MEFs of wild-type littermates. Both cell types were incubated with 10–7 M budesonide or DMSO for 3 h and then treated in the absence or presence of TNF-{alpha} (10 ng/ml) for 1 h.

Data were first analyzed with a principal components analysis (PCA), a statistical method for displaying the global relationship of the array data among experimental condition (Fig. 2). Clustering of microarray-derived gene patterns on a PCA diagram reflects the inherent kinship, or otherwise, of their genetic profiles, by measuring true differences in data sets (50). In WT cells, the four treatments separate out as distinct clusters on the PCA diagram, indicating that a distinct genotypic signature for each experimental condition is recognizable at the microarray level. The cluster of budesonide plus TNF-{alpha} falls in between the two clusters of budesonide and TNF-{alpha}, showing a distinctly graded effect of TNF-{alpha}. In the TTP–/– data set, however, the cluster of budesonide plus TNF-{alpha} is closer to TNF-{alpha}, implying that budesonide has lesser effect than in WT cells. Also the distinct separation between the four groups visible in the WT data sets is diminished. These findings provide a first indication of the role of TTP in determining the changes in gene expression that separate these experimental conditions.


Figure 2
View larger version (44K):
[in this window]
[in a new window]

  		FIGURE 2. Patterns of differential regulation of gene expression in WT and TTP–/– MEFs. A, PCA of array data. Gene expression in WT and TTP–/– MEFs treated with DMSO, budesonide, TNF-{alpha}, or budesonide (Bud) and TNF-{alpha}. Clustering of microarrays on a PCA diagram reflects the inherent kinship, or otherwise, of their genetic profiles. B, Heat maps of the array data sets from WT or TTP–/– cells (n = 3). For all conditions depicted, up-regulated genes are shown in red and down-regulated genes in green. Gene expression profile for all named and present genes found in WT and TTP–/– MEFs treated with DMSO (D), TNF-{alpha} (T), budesonide (B), budesonide and TNF-{alpha} (BT). C, Each column of the heat map represents the mean data for each treatment minus DMSO control. Brackets highlight examples of specific differences in gene regulation in TTP–/– cells (see Results).

 
Profound global changes in gene expression in the TTP–/–, both at baseline and in response to treatment, can be further appreciated from the heat map of the array data by comparison with the data from the WT. The heat map in Fig. 2B clearly shows the pleiotropic phenotypic effect of this single gene deletion. Baseline gene expression is altered in TTP–/– cells, as well as the response to treatment with either budesonide, TNF-{alpha}, or their combination. The latter effects are highlighted in the heat map shown in Fig. 2C, which illustrates the changes in global gene expression in WT and TTP–/– MEFs in response to budesonide and TNF-{alpha} treatment.

In the analysis of the array data, we compared budesonide-treated samples with DMSO-treated samples in the absence of TNF-{alpha} (B-D) to assess the effect of GCs in the absence of an inflammatory stimulus. We then analyzed the changes in gene expression induced by TNF-{alpha} over the DMSO-treated, unstimulated cells (T-D), so that we could compare the effect of budesonide treatment in TNF-{alpha}-stimulated cells vs TNF-{alpha} alone (BT-T), to identify TTP-dependent changes in the antagonistic effects of GCs on TNF-{alpha}-driven gene expression. As shown in Fig. 2C, stimulus-induced changes leading to either up-regulation of down-regulation of gene expression in WT cells are lost for a large number of genes in the TTP–/– MEFs. However, WT and TTP–/– MEFs importantly retain for a subset of genes a common response to TNF-{alpha}, demonstrating a conservation of gene expression despite the loss of TTP.

Importantly, the global changes in gene expression observed following GC treatment in WT MEFs, as well as the identity of the genes affected, were consistent with the known functional profile of GC action, which produces concomitant suppression of proinflammatory factors and induction of genes involved in homeostatic, innate immune, and metabolic functions. These data, together with the highly distinct clustering on the PCA, confirms the reliability of this cell line as a model of GC action.

The total number of genes significantly modified in WT cells by the indicated treatments (shown in the horizontal bar graphs in Fig. 3) was dramatically reduced in TTP–/– cells, with the greatest loss in GC sensitivity for genes whose expression was down-regulated in WT by GCs. Using Venn diagrams to dissect the relationship between the two datasets, only 5 of the 145 genes down-regulated by budesonide in WT were still comparably repressed in TTP–/– cells (Fig. 3A), accounting for a 97% loss of response to GCs. A small subset of genes (n = 11) showed a significant increase in GC-mediated inhibition of expression in TTP–/– cells compared with WT. Interestingly, the induction of gene expression by GCs in WT was blunted in TTP–/– cells by 89%, with only 19 of 172 GC-induced genes showing changes comparable to the WT. Besides this significant loss in GC-induced response, 34 genes either became up-regulated after GC treatment or increased their GC-mediated induction only in TTP–/– cells. Also, TNF-{alpha}-dependent responses in the absence of budesonide were globally affected, with a loss of 94% of the down-regulated and 75% of the up-regulated genes (Fig. 3B). Given the strong influence of TTP in TNF-{alpha}-induced gene expression, we focused the analysis of GC antagonism on TNF-{alpha}-regulated genes on those for which significant expression by TNF-{alpha} was present in both WT and TTP–/–. Genes with a Z ratio difference of three or more, which represents a change of three SDs, between cells treated with TNF-{alpha} alone and cells treated with TNF-{alpha} plus budesonide were considered antagonized by GCs. There were eight genes for which, fulfilling these criteria, the antagonistic effect of budesonide was lost in TTP–/– (Fig. 3C). As expected, even in such a small sample the genes affected were mostly related to inflammation, including chemokines (CCL2, CCL7, CXC3CL1), the adhesion molecule VCAM-1, and TLR2. These data indicate an unprecedented, central role of TTP in mediating GC and, to a lesser extent, TNF-{alpha}-mediated effects.


Figure 3
View larger version (20K):
[in this window]
[in a new window]

  		FIGURE 3. Loss of GC sensitivity and of TNF-{alpha} response in TTP–/– MEFs. Changes in gene expression in WT vs TTP –/– cells upon exposure to (A) budesonide (Bud) and (B) TNF-{alpha}. For each experimental condition, the horizontal bar plots represent the total number of genes significantly affected (n = genes listed at the far end of the bars). The Venn diagrams below the bar graphs illustrate, for each treatment, the relationships between genes down-regulated (italics, arrow {downarrow}) and up-regulated (bold, arrow {uparrow}), in WT vs TTP–/– MEFs. The full list of affected genes for each category is provided in files S1 and S2 in the supplemental material. C, Loss of budesonide antagonism of TNF-{alpha}-induced genes in TTP–/–. Shown is the Z ratio of genes up-regulated by TNF-{alpha} treatment in both WT and TTP–/–. Budesonide antagonism was determined by a Z-ratio difference of three or more between cells treated with TNF-{alpha} alone or plus budesonide.

 
A complete list of the gene profiles shown in Fig. 2, ranked according to the value of Z ratios after treatment in WT cells and showing the corresponding Z ratio in TTP–/– cells is provided in the online supplementary material (files S1 to S3). The most significant changes in gene expression in budesonide-treated WT and TTP–/– MEFs are shown in Tables I and II, while those occurring in TNF-{alpha}-treated cells are shown in Table III.

Nine genes were selected for single gene validation by real-time PCR, based on highly significant Z ratios and the large magnitude of change in expression displayed in TTP–/– cells (Fig. 4). For six important inflammatory genes (CCL7, CXCL1, CCL2, CXCL5, CXCL7, MMP-9), we confirmed the significant down-regulation by budesonide in WT, but not TTP–/–, MEFs (Fig. 4A). Similarly, Serpina3n mRNA was induced by GCs in WT but not in TTP–/– cells, consistent with results of the array. We also validated induction of CCL5 and IL-6 by TNF-{alpha} in WT but not in TTP–/– cells (Fig. 4B).


Figure 4
View larger version (15K):
[in this window]
[in a new window]

  		FIGURE 4. Validation of array-based changes in gene expression by real-time PCR. Each plot represents fold changes of RNA levels for each gene in WT and TTP–/– cells: A, budesonide vs DMSO; B, TNF-{alpha} vs DMSO control (n = 3, p < 0.05 for all data, WT vs TTP–/–).

 
Functional classification of GC-sensitive, TTP-dependent genes

Genes for whom response to GC treatment was affected in TTP–/– cells (Fig. 3A) were subjected to GO classification (Table IV). A significant percentage of these genes are involved in immunity and signal transduction, biological processes that are chiefly targeted by GCs for their anti-inflammatory action. Involvement of TTP in the effect of GCs on genes important for metabolism and cell development indicate that TTP is likely to mediate other homeostatic and nonimmune functions driven by GCs.

Association of GC-sensitive transcripts with TTP and role of TTP on mRNA decay

We then tested whether budesonide-induced TTP, to convey GC action, would associate with endogenous mRNAs, and whether it would exert its effects by modulating transcript stability. To test this hypothesis, wild-type MEFs were treated with 10–7 M budesonide for 3 h, and RNP complexes were immunoprecipitated from cytoplasmic lysates using a rabbit polyclonal anti-TTP Ab or an isotype-matched Ab as control. Western blot showed that TTP was selectively immunoprecipitated using the anti-TTP Ab, whereas no immunoreactive TTP band is observed using the isotype control Ab (Fig. 5A). Subsequently, mRNA isolated from the IP was used to quantify, by real-time PCR, the enrichment of selected mRNAs (Fig. 5B). For this analysis, we selected the genes that were validated by PCR, because their expression showed both highly significant GC-induced modulation and strong TTP dependence, and were thus reasonable candidates for TTP binding. For the quantitation of the enrichment of specific mRNAs after mRNP-IP, the difference of cycles in the CT value between the TTP and the control IP ({Delta}CT) indicated a 2–(–{Delta}CT) = fold enrichment in target mRNA in the TTP IP (43). Of the 11 transcripts analyzed, 6 showed a significant enrichment in the IP done with the anti-TTP over that performed with the IgG control, indicating association of these endogenous mRNAs with TTP. The chemokine CXCL1 showed the greatest fold enrichment, followed by CCL2, CCL7, IL-6, CXCL5, and MMP9 (Fig. 5C). Importantly, 5 of the 6 transcripts enriched in the TTP IP display multiple AREs in their 3'-UTR (table S1 in the online supplementary material). The remaining 5 transcripts showed very small or no difference between the two IP conditions, in a range similar to that displayed by β-actin, GAPDH, and 18s mRNA, which we used as negative control for the relative lack of specific enrichment despite the more abundant message, indicated by the lower CT number (Fig. 4B, 18s mRNA).


Figure 5
View larger version (22K):
[in this window]
[in a new window]

  		FIGURE 5. Immunoprecipitation of endogenous mRNA-TTP complexes. A, Western blot of cytoplasmic lysate of WT MEFs demonstrating specific IP of TTP. B, Representative real-time PCR amplification plot of fluorescence intensity over background ({Delta}Rn) against PCR cycle (CT) showing enrichment of CXCL1 and IL-6 mRNA, but not of serpin3a and 18S RNA transcripts, in lysates of GC-treated MEFs subjected to IP with an anti-TTP Ab (filled symbols) vs the IP with the isotype-matched Ab (open symbols). C, Fold enrichment of transcripts immunoprecipitated by the anti-TTP relative to transcript detection in the isotype Ab IP control (fold values indicated on top). Of the 11 transcripts tested, 6 (gray bars) contain multiple AREs (3'-UTR sequences available in table S1.C in the online supplemental material). Mean ± SEM of n = 3; *, p < 0.05; **, p < 0.003 vs IgG isotype control.

 
Given the association of these GC-sensitive transcripts with TTP, which is functionally known as an mRNA decay-promoting RBP, we investigated whether GC would accelerate the mRNA decay of the TTP-associated targets and whether this process was impaired in TTP–/– cells. Experiments with Act D (Fig. 6) showed that in WT MEFs, GC induced acceleration of CCL7 mRNA. In fact, the transcript’s half life (t(1/2))—calculated for each condition as the time (hours) required for the transcript to decrease to 50% of its initial abundance—was significantly decreased in cells treated with budesonide as compared with DMSO (0.9 ± 0.04 h vs 1.4 ± 0.2 h, respectively, p = 0.02). This effect was abolished in TTP–/– MEFs, in which the half-life of CCL7 mRNA in GC-treated cells was similar to that detected in DMSO-treated cells. Consequently, the half-lives in WT and TTP–/– cells treated with budesonide were significantly different (0.9 ± 0.04 h vs 1.7 ± 0.2 h, respectively, p = 0.04), demonstrating that TTP is needed for GC-induced acceleration of CCL7 mRNA decay. Similarly, TTP appears to be necessary to convey enhanced degradation of CCL2 mRNA under GC treatment (half-life of 1.0 ± 0.1 h in WT, 1.5 ± 0.2 h in TTP–/–, p = 0.02).


Figure 6
View larger version (19K):
[in this window]
[in a new window]

  		FIGURE 6. Determination of mRNA decay of selected transcripts by real-time PCR. mRNA levels for the indicated genes were detected by real-time PCR in WT or TTP–/– MEFs stimulated with budesonide or DMSO (n = 5) after treatment with Act D. Results are shown as the percent of mRNA at time 0. For each mRNA, the bar graph insets indicate the half-life (t(1/2), in h) in each condition. Mean ± SEM of n = 5; *, p < 0.05.

 
The decay of CXCL5 RNA was affected differently by the lack of TTP. Significant differences in RNA levels between WT and TTP–/– cells were noticeable already in DMSO-treated cells at 3 and 5 h after transcriptional shutoff (at 5 h, 55 ± 14% of control remained in WT vs 9 ± 3% in TTP–/– cells, p = 0.04), resulting in a much shorter mRNA half-life in DMSO-treated TTP–/– cells vs WT MEFs (1.3 ± 0.2 h vs 9.1 ± 3.2 h, respectively). Therefore, it appears that loss of TTP affects GC response as part of a more global defect.

Interestingly, the rate of IL-6 mRNA decay was not changed by GC treatment in WT MEFs, nor was it affected in budesonide-treated TTP–/– MEFs despite the strong association with TTP of the IL-6 mRNA. Half-lives for each of the conditions were therefore almost superimposable (1.2 ± 0.1 h vs 1.2 ± 0.12 h in DMSO-treated WT and TTP–/–MEFs, respectively; 1.1 ± 0.2 h vs 1.3 ± 0.3 h in budesonide-treated WT and TTP–/– MEFs, p = NS). Similar results were obtained for CXCL1 (data not shown).

Analysis of CXCL7, CCL5, and serpina3n mRNA turnover could not be pursued with this experimental system, as treatment with Act D resulted in artifactual stabilization of the transcripts (100% of the RNAs present after 5 h treatment) (data not shown). Despite a low but consistent enrichment after RNP-IP of the housekeeping β-actin and GAPDH mRNA, their steady state levels and decay rates were unchanged by Act D treatment and between cell types (data not shown).

Effect of silencing of TTP in WT MEFs on GC response

To verify whether the different GC sensitivity of TTP-bound targets observed between the WT and TTP–/– cells could be reproduced in a model of acute suppression of TTP, we inhibited TTP expression in WT MEFs using an RNAi assay. WT MEFs were transiently transfected with two TTP-specific siRNA (SiRNA1 and 2), and the effect of the TTP silencing on expression of CCL7, CCL2, CXCL5, and IL-6 after GC treatment was compared with the effect of GC treatment on the expression of these genes in cells transfected with a scrambled siRNA. We consistently observed by Western blot a loss of TTP expression in cells treated with the two TTP siRNA. Inhibition of TTP was paralleled by a partial but consistent loss of the GC inhibition of the four transcripts present in scrambled-transfected cells, which became significant in cells transfected with the siRNA inducing maximal TTP suppression (SiRNA1, 16.5 ± 2.9% of budesonide-induced TTP in cells transfected with scrambled siRNA) (Fig. 7A).


Figure 7
View larger version (16K):
[in this window]
[in a new window]

  		FIGURE 7. RNAi of TTP and the effects on selected transcripts. A, Representative Western blot of TTP expression in WT MEFs stimulated with DMSO or budesonide following transient transfection with an siRNA specific for TTP and a control scrambled siRNA (Sc). Bar graph below represents the densitometric values (mean ± SEM of n = 3) of the normalized TTP bands expressed as a percent of budesonide-induced TTP. B, Inhibition of gene expression in budesonide-treated WT MEFs over expression in DMSO-treated cells assessed by real-time PCR. #, p < 0.05 vs DMSO-treated cells Sc transfectants; *, p < 0.05 vs budesonide-treated Sc.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Disclosures
 References
 
Mounting evidence indicates that GCs modulate gene expression far beyond transcriptional regulation, but the molecular signature of GC effect on posttranscriptional regulation has been only partially revealed. In particular, little is known on the effect of GCs on the complex biology of the ARE-binding proteins, which act downstream the kinase signaling cascades and ultimately convey the stimulus-driven changes in mRNA turnover, by recruiting or inhibiting the enzymatic complexes responsible for mRNA deadenylation and decay.

In the present study, we report that the ARE-binding protein TTP is a critical mediator of GC action, as global gene regulation exerted by GCs was severely blunted in MEFs cells isolated from TTP–/– mice while conserved in the WT littermates. Similar effects on the expression of select genes were observed by targeted disruption of TTP by siRNA in WT MEFs.

We found TTP to be inducible by GCs in primary and immortalized airway epithelium, providing evidence for a more direct control of posttranscriptional gene regulation by GC in a relevant therapeutic cell target. Induction of TTP was reproducible in MEFs, in line with data showing up-regulation of TTP in mice tissues after GC administration in vivo (35). This allowed us to use MEFs from TTP–/– mice to characterize the relevance of TTP in the global changes in gene expression mediated by GCs. It is interesting to note that TTP is inducible by both proinflammatory stimuli like TNF-{alpha} as well as by anti-inflammatory signals like GCs, likely due to its function as a central regulator in the expression of genes involved in inflammation.

Comparison of the gene expression profile elicited by GCs in WT and TTP–/– MEFs revealed for the first time a striking dependence of the GCs response on TTP, indicating that the impact of posttranscriptional regulation in the mechanism of action of GCs is larger than ever appreciated, and supporting the relevance of the GC-driven induction of anti-inflammatory genes (6, 51).

Inhibition of chemokine expression is considered a major factor in the suppressive action of GCs on adaptive immune responses (1). The strong antagonistic effect of GCs on chemokine expression, which was detected in GC-treated WT MEFs both in TNF-{alpha}-stimulated and at baseline, was one of the most affected by the lack of TTP. Loss of significant GC inhibition of adhesion molecules, like VCAM-1, further points at TTP as an essential molecular component of one of the main mechanism of anti-inflammatory action of GCs, the inhibition of inflammatory cell recruitment (1).

Based on the hypothesis that TTP would mediate mRNA destabilization, it was somewhat expected that lack of TTP would impact, to some degree, the ability of GCs to inhibit gene expression. With regard of genes induced by GCs, according to this proposed mode of action, loss of TTP could be expected to increase their steady state levels due to lack of mRNA destabilization. Instead, in TTP–/– MEFs we found a loss, or else a significant decrease, in the expression of genes induced by GCs in WT cells. Some of the genes for which GC-driven induction was lost in TTP–/– MEFs are involved in the response of the acute phase of inflammation, such as the serine protease inhibitors (serpins) and orosomucoid, or display potent anti-inflammatory activity like metallothionein-2, which acts as a potent cytoprotective and antioxidant agent and inhibits the expression of inflammatory chemokines and cytokines (52, 53). This target profile underlines how TTP participates also to the modulation of the innate immune response by GCs (5).

The mechanism by which TTP mediates the GC response is bound to be complex, involving both direct effects, likely mediated by binding of TTP to discrete AREs, as well as indirect effects. In probing such a complex system, we found the association of TTP with just 6 of 11 of the transcripts whose differential response to GCs in TTP–/– cells had been validated. These transcripts—CXCL1, CCL7, CCL2, IL-6, CXCL5, and MMP-9—all contain AUUUA pentamers or UUAUUUAUU nonamers in the 3'-UTRs that are compatible with TTP binding (54), although in different number and sequence contexts (supplemental table S1). The transcripts showing no association with TTP by mRNP-IP, despite profound changes in GC sensitivity in TTP–/– cells, displayed instead only one or none of these sequences in the 3'-UTRs, with the noticeable exception of EGR-1 mRNA, which bears two UAUUUAU heptamers in a highly A/U-rich milieu (supplemental table S1). As RBPs mediate changes in mRNA turnover in a dynamic fashion, it is likely that association of TTP with its targets would change over time and therefore could be missed in a single time point experiment. It is well-established that the context of the 3'-UTR sequence where AREs are embedded, the secondary structure of the entire transcript, and the ionic milieu of the cell environment are key determinants of the specific binding and the on-off rate of regulatory proteins. Consideration of all these factors will be needed to proceed to more in-depth investigations to define the molecular interface between TTP and its targets and its role in mediating GC response.

Along the same lines, the results from our experiments with Act D support only in part, at least in the condition tested, the assumption that association with TTP would accelerate the decay of the targeted transcripts upon GC treatment, but rather implicate that TTP would participate to a GC-induced remodeling of the RNP complex leading to different functional outcomes. For CCL7 and CCL2 mRNA, the acceleration of mRNA decay induced by GC in WT MEFs was indeed lost in TTP–/– cells, in line with the original hypothesis; however, CXCL5 mRNA displayed in DMSO-treated WT MEFs a much longer half-life as compared with that in TTP–/– cells, indicating that in this condition, TTP participates to a turnover mechanism with a final outcome of relative stabilization. The inhibitory effect of GC on CXCL5 seems to be lost in TTP–/– cells as a consequence to the loss of this function. Yet another different outcome was observed for the turnover of IL-6 mRNA, which was not modified by either GC treatment or by lack of TTP despite significant enrichment in the RNP-IP assay and the presence of a 3'-UTR extremely rich in AREs (supplemental table S1). For the latter reason, as well as for the clear TTP dependence of the GC responsiveness of this transcript, we deem it unlikely that IL-6 mRNA would become associated with TTP only during the preparation of cell extracts for the RNP-IP analysis.

Such differences might be in part due to the limitation of the experimental model used. Act D arrests the global transcriptional activity of the cell, and inducible or labile regulatory factors, possibly transcript-specific, may be absent or degraded, altering the physiological mRNA turnover rates. Moreover, nuclear export of mRNA is coupled to ongoing gene transcription in mammalian cells (55), as it is the nuclear reaccumulation following nucleocytoplasmic shuttling of several important mRNA-binding proteins, including HuR (56, 57, 58, 59). These factors may have critically affected the decay rate of CXCL7, CCL5, and serpina3n mRNAs following Act D treatment.

Besides the assay’s limitations, however, our data clearly underscore complex interactions between GC treatment and the role of TTP in regulating gene expression. The results obtained for CXCL5 and IL-6 mRNA turnover, as well as the concomitant loss of GC-induced gene expression in TTP–/– cells clearly raises the possibility that TTP could have a more pleiotropic function than previously appreciated. Dynamic interplay of TTP with other RNA-binding factors, rather than direct binding to AREs, may ultimately be responsible for a role of TTP in increased transcript stabilization. In a recent study, TTP has been found unable to bind to the ARE-bearing INOS mRNA, and to interact instead with the KH-type splicing regulatory protein, another ARE-binding protein that bound to INOS mRNA, mediating its decay. Under proinflammatory stimulation, such protein-protein interaction would therefore "dislodge" KH-type splicing regulatory protein and the associated exosome and allow binding for HuR, which mediates INOS mRNA stabilization (31). An RNA-independent, mRNA-stabilizing function of TTP had been first observed in TTP mutants lacking RNA-binding function, which were found to increase the half-life of known TTP targets such as TNF-{alpha} (60). Many of the transcripts found in this study to be up-regulated by GCs in a TTP-dependent manner do display AREs and could be therefore suitable candidates for testing the hypothesis that TTP mediates GC action through a complex remodeling of RNP complexes. Along the same lines, the lack of AREs in other genes whose sensitivity to GCs was significantly affected in TTP–/– cells indicate the presence of yet undiscovered mechanisms of GC-driven gene regulation by TTP, either dependent from binding to cis elements distinct from AREs or due to protein-protein regulatory interactions. Along these lines, it is important to underscore the participation of TTP to the formation of processing bodies, which are distinct cytoplasmic sites of RNP complexes where mRNAs targeted for decay are transiently sequestered from translation (61). In this case, TTP could promote mRNA sequestration and decay independently from direct contact with the mRNA.

Regardless of the mechanism, the TTP-mediated effect can also be vastly amplified indirectly, for example, in case the affected gene is a regulatory protein—a transcription factor, a signaling molecule, etc.—by the loss of its target’s downstream function. Transcription factors are often expressed as early response genes and display fast transcript decay rates (62). We found that GC inhibition of proinflammatory transcription factors, like the NF-{kappa}B molecular species NF-{kappa}B1 and early growth response (Egr)-1 (63, 64, 65) was abolished in TTP–/– cells (Table I). The early response, ARE-bearing gene Egr-1 encodes for a transcription factor that mediates tissue inflammation and remodeling by promoting the expression of multiple genes involved in inflammation, apoptosis, and matrix production (64, 65). Consistent with a potential regulatory role of TTP, inhibition of Egr-1 by dexamethasone was reported to occur posttranscriptionally in a myelomonocytic cell line (66). The role of TTP in mediating the inhibition of Egr-1 by GCs would indirectly determine the GC-mediated inhibition of multiple Egr-1-dependent proinflammatory genes, indicating how regulation of mRNA turnover can also indirectly affect transcriptional control of multiple genes. More studies will be needed to elucidate the pathways mediating such indirect TTP actions.

Despite the different effect of the lack of TTP on targets’ mRNA turnover, the loss of GC-induced repression of those genes—CCL2, CCL7, CXCL5, and IL-6—that demonstrated TTP binding was also reproducible, although by different degree, following silencing of TTP by siRNA in WT MEFs. Despite differences between this model and the TTP KO-derived cells, due different level of TTP repression and to the diverse phenotype of cells carrying chronic vs acute factor depletion, these data indicate the relevance of TTP in GC action beyond the TTP–/– mouse model. In line with these results and in additional support of the potential relevance of this mechanism beyond the model we tested and in human biology, Smoak and Cidlowski (35) report the partial loss of dexamethasone-induced down-regulation of TNF-{alpha} in human airway epithelial cell line A549 where TTP was suppressed by stable transfection of a TTP short hairpin RNA. Although induction of TTP after in vivo administration of GC has been documented in several mouse tissues (35), in vitro treatment of mouse macrophages with GC is reported to inhibit LPS-induced TTP expression (67), suggesting tissue-specificity of TTP regulation possibly linked to the protective effect of GC treatment on innate immune responses.

Along with studies on the mechanism of TTP-mediated GC response, it is pressing to identify TTP regulation in clinical settings where GCs are administered, and to investigate dysregulation of GC-driven TTP expression or function as a possible mechanism of steroid resistance. It can be envisioned that mutations affecting the levels of TTP or its ARE-binding ability could greatly impair GC action. To this end, multiple single nucleotide polymorphisms have been identified in the human TTP gene (68).

Our genome-wide approach provides convincing evidence that the role of posttranscriptional gene regulation in GC response is much larger than previously appreciated, and point at TTP as a key mediator in this process, hence having far-reaching implications in our understanding of the pathogenesis and treatment of inflammatory diseases.


   Acknowledgments
 
We thank Drs. Perry J. Blackshear and Wi Lai (National Institutes of Environmental Health Sciences, Research Triangle Park, NC) for providing the WT and TTP KO MEFs. We thank Dr. Vinayakumar V. Prabhu (Gene Expression and Genomics Unit, National Institute of Aging, National Institutes of Health, Baltimore, MD) for his skillful assistance in the data analysis of the array study.


   Disclosures
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
References
 
The authors have no financial conflict of interest.


   Footnotes
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 This work was supported by National Institutes of Health Grant R01 AI060990-01A1 (to C.S.). F.T.I. was the recipient of the 2007 Strategic Training in Allergy Research (ST*AR) Award from the American Academy of Allergy, Asthma, and Immunology. M.G. was supported by the National Institute on Aging–Intramural Research Program, National Institutes of Health. Back

2 Address correspondence and reprint requests to Dr. Cristiana Stellato, Johns Hopkins Asthma and Allergy Center, 5501 Hopkins Bayview Circle, Room 1A.12A, Baltimore, MD 21224. E-mail address: stellato{at}jhmi.edu Back

3 Abbreviations used in this paper: GC, glucocorticoid; GR, GC receptor; ARE, adenylate/uridylate-rich region; UTR, untranslated region; KO, knockout; TTP, tristetraprolin; RBP, RNA-binding protein; INOS, inducible NO synthase; MEF, mouse embryonic fibroblast; PBEC, primary bronchial epithelial cell; WT, wild type; Act D, actinomycin D; IP, immunoprecipitation; CT, cycle threshold; GO, gene ontology; RNP, ribonucleoprotein; mRNP, messenger RNP; RNAi, RNA interference; PCA, principal component analysis; Egr-1, early growth response-1; PTR, posttranscriptional regulation; siRNA, small interfering RNA. Back

4 The online version of this article contains supplemental material. Back

Received for publication July 13, 2007. Accepted for publication April 3, 2008.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
 References
 

  1. Schleimer, R. P.. 1998. Glucocorticosteroids: their mechanisms of action and use in allergic diseases. C. E. R. E. Middleton, and E. F. Ellis, and J. N. F. Adkinson, and J. W. Yunginger, and W. Busse, eds. Allergy: Principles and Practice 638-660. Mosby, St. Louis.
  2. Rhen, T., J. A. Cidlowski. 2005. Antiinflammatory action of glucocorticoids: new mechanisms for old drugs. N. Engl. J. Med. 353: 1711-1723. [Free Full Text]
  3. Stellato, C.. 2004. Post-transcriptional and nongenomic effects of glucocorticoids. Proc. Am. Thorac. Soc. 1: 255-263. [Abstract/Free Full Text]
  4. Necela, B. M., J. A. Cidlowski. 2004. Mechanisms of glucocorticoid receptor action in noninflammatory and inflammatory cells. Proc. Am. Thorac. Soc. 1: 239-246. [Free Full Text]
  5. Schleimer, R. P.. 2004. Glucocorticoids suppress inflammation but spare innate immune responses in airway epithelium. Proc. Am. Thorac. Soc. 1: 222-230. [Abstract/Free Full Text]
  6. Clark, A. R.. 2007. Anti-inflammatory functions of glucocorticoid-induced genes. Mol. Cell. Endocrinol. 275: 79-97. [Medline]
  7. Adcock, I. M., K. Ito, P. J. Barnes. 2004. Glucocorticoids: effects on gene transcription. Proc. Am. Thorac. Soc. 1: 247-254. [Abstract/Free Full Text]
  8. Barnes, P. J.. 2006. Corticosteroid effects on cell signalling. Eur. Respir. J. 27: 413-426. [Abstract/Free Full Text]
  9. Clark, A.. 2000. Post-transcriptional regulation of pro-inflammatory gene expression. Arthritis Res. 2: 172-174. [Medline]
  10. Garneau, N. L., J. Wilusz, C. J. Wilusz. 2007. The highways and byways of mRNA decay. Nat. Rev. Mol. Cell Biol. 8: 113-126. [Medline]
  11. Kracht, M., J. Saklatvala. 2002. Transcriptional and post-transcriptional control of gene expression in inflammation. Cytokine 20: 91-106. [Medline]
  12. Gaestel, M.. 2006. MAPKAP kinases–MKs–two’s company, three’s a crowd. Nat. Rev. Mol. Cell Biol. 7: 120-130. [Medline]
  13. Stoecklin, G., P. Anderson. 2006. Posttranscriptional mechanisms regulating the inflammatory response. K. F. A. Frederick, and W. Alt, and T. Honjo, and F. Melchers, and J. W. Uhr, and E. R. Unanue, eds. Advances in Immunology 1-37. Academic Press, San Diego.
  14. Hollams, E. M., K. M. Giles, A. M. Thomson, P. J. Leedman. 2002. MRNA stability and the control of gene expression: implications for human disease. Neurochem. Res. 27: 957-980. [Medline]
  15. Chen, C. Y., A. B. Shyu. 1995. AU-rich elements: characterization and importance in mRNA degradation. Trends Biochem. Sci. 20: 465-470. [Medline]
  16. Wilusz, C. J., J. Wilusz. 2004. Bringing the role of mRNA decay in the control of gene expression into focus. Trends Genet. 20: 491-497. [Medline]
  17. Khabar, K. S.. 2005. The AU-rich transcriptome: more than interferons and cytokines, and its role in disease. J. Interferon Cytokine Res. 25: 1-10. [Medline]
  18. Bakheet, T., B. R. Williams, K. S. Khabar. 2006. ARED 3.0: the large and diverse AU-rich transcriptome. Nucleic Acids Res. 34: D111-114. [Abstract/Free Full Text]
  19. Guhaniyogi, J., G. Brewer. 2001. Regulation of mRNA stability in mammalian cells. Gene 265: 11-23. [Medline]
  20. Dreyfuss, G., V. N. Kim, N. Kataoka. 2002. Messenger-RNA-binding proteins and the messages they carry. Nat. Rev. Mol. Cell Biol. 3: 195-205. [Medline]
  21. Carrick, D. M., W. S. Lai, P. J. Blackshear. 2004. The tandem CCCH zinc finger protein tristetraprolin and its relevance to cytokine mRNA turnover and arthritis. Arthritis Res. Ther. 6: 248-264. [Medline]
  22. Worthington, M. T., J. W. Pelo, M. A. Sachedina, J. L. Applegate, K. O. Arseneau, T. T. Pizarro. 2002. RNA binding properties of the AU-rich element-binding recombinant Nup475/TIS11/tristetraprolin protein. J. Biol. Chem. 277: 48558-48564. [Abstract/Free Full Text]
  23. Blackshear, P. J., W. S. Lai, E. A. Kennington, G. Brewer, G. M. Wilson, X. Guan, P. Zhou. 2003. Characteristics of the interaction of a synthetic human tristetraprolin tandem zinc finger peptide with AU-rich element-containing RNA substrates. J. Biol. Chem. 278: 19947-19955. [Abstract/Free Full Text]
  24. Brewer, B. Y., J. Malicka, P. J. Blackshear, G. M. Wilson. 2004. RNA sequence elements required for high affinity binding by the zinc finger domain of tristetraprolin: conformational changes coupled to the bipartite nature of AU-rich mRNA-destabilizing motifs. J. Biol. Chem. 279: 27870-27877. [Abstract/Free Full Text]
  25. Blackshear, P. J.. 2002. Tristetraprolin and other CCCH tandem zinc-finger proteins in the regulation of mRNA turnover. Biochem. Soc. Trans. 30: 945-952. [Medline]
  26. Carballo, E., W. S. Lai, P. J. Blackshear. 1998. Feedback inhibition of macrophage tumor necrosis factor-{alpha} production by tristetraprolin. Science 281: 1001-1005. [Abstract/Free Full Text]
  27. Carballo, E., W. S. Lai, P. J. Blackshear. 2000. Evidence that tristetraprolin is a physiological regulator of granulocyte-macrophage colony-stimulating factor messenger RNA deadenylation and stability. Blood 95: 1891-1899. [Abstract/Free Full Text]
  28. Sawaoka, H., D. A. Dixon, J. A. Oates, O. Boutaud. 2003. Tristetraprolin binds to the 3'-untranslated region of cyclooxygenase-2 mRNA: a polyadenylation variant in a cancer cell line lacks the binding site. J. Biol. Chem. 278: 13928-13935. [Abstract/Free Full Text]
  29. Stoecklin, G., B. Gross, X. F. Ming, C. Moroni. 2003. A novel mechanism of tumor suppression by destabilizing AU-rich growth factor mRNA. Oncogene 22: 3554-3561. [Medline]
  30. Ogilvie, R. L., M. Abelson, H. H. Hau, I. Vlasova, P. J. Blackshear, P. R. Bohjanen. 2005. Tristetraprolin down-regulates IL-2 gene expression through AU-rich element-mediated mRNA decay. J. Immunol. 174: 953-961. [Abstract/Free Full Text]
  31. Fechir, M., K. Linker, A. Pautz, T. Hubrich, U. Forstermann, F. Rodriguez-Pascual, H. Kleinert. 2005. Tristetraprolin regulates the expression of the human inducible nitric-oxide synthase gene. Mol. Pharmacol. 67: 2148-2161. [Abstract/Free Full Text]
  32. Lai, W. S., J. S. Parker, S. F. Grissom, D. J. Stumpo, P. J. Blackshear. 2006. Novel mRNA targets for tristetraprolin (TTP) identified by global analysis of stabilized transcripts in TTP-deficient fibroblasts. Mol. Cell. Biol. 26: 9196-9208. [Abstract/Free Full Text]
  33. Jalonen, U., R. Nieminen, K. Vuolteenaho, H. Kankaanranta, E. Moilanen. 2006. Down-regulation of tristetraprolin expression results in enhanced IL-12 and MIP-2 production and reduced MIP-3{alpha} synthesis in activated macrophages. Mediators Inflamm. 6: 40691
  34. Taylor, G. A., E. Carballo, D. M. Lee, W. S. Lai, M. J. Thompson, D. D. Patel, D. I. Schenkman, G. S. Gilkeson, H. E. Broxmeyer, B. F. Haynes, P. J. Blackshear. 1996. A pathogenetic role for TNF {alpha} in the syndrome of cachexia, arthritis, and autoimmunity resulting from tristetraprolin (TTP) deficiency. Immunity 4: 445-454. [Medline]
  35. Smoak, K., J. A. Cidlowski. 2006. Glucocorticoids regulate tristetraprolin synthesis and posttranscriptionally regulate tumor necrosis factor {alpha} inflammatory signaling. Mol. Cell Biol. 26: 9126-9135. [Abstract/Free Full Text]
  36. Stellato, C.. 2007. Glucocorticoid actions on airway epithelial responses in immunity: functional outcomes and molecular targets. J. Allergy Clin. Immunol. 120: 1247-1263. quiz 1264–1265.
  37. Eddleston, J., J. Herschbach, A. L. Wagelie-Steffen, S. C. Christiansen, B. L. Zuraw. 2007. The anti-inflammatory effect of glucocorticoids is mediated by glucocorticoid-induced leucine zipper in epithelial cells. J. Allergy Clin. Immunol. 119: 115-122. [Medline]
  38. Imasato, A., C. Desbois-Mouthon, J. Han, H. Kai, A. C. Cato, S. Akira, J. D. Li. 2002. Inhibition of p38 MAPK by glucocorticoids via induction of MAPK phosphatase-1 enhances nontypeable Haemophilus influenzae-induced expression of Toll-like receptor 2. J. Biol. Chem. 277: 47444-47450. [Abstract/Free Full Text]
  39. Churchill, L., B. Friedman, R. P. Schleimer, D. Proud. 1992. Production of granulocyte-macrophage colony-stimulating factor by cultured human tracheal epithelial cells. Immunology 75: 189-195. [Medline]
  40. Reddel, R. R., S. E. Salghetti, J. C. Willey, Y. Ohnuki, Y. Ke, B. I. Gerwin, J. F. Lechner, C. C. Harris. 1993. Development of tumorigenicity in simian virus 40-immortalized human bronchial epithelial cell lines. Cancer Res. 53: 985-991. [Abstract/Free Full Text]
  41. Lal, A., K. Mazan-Mamczarz, T. Kawai, X. Yang, J. L. Martindale, M. Gorospe. 2004. Concurrent versus individual binding of HuR and AUF1 to common labile target mRNAs. EMBO J. 23: 3092-3102. [Medline]
  42. Heid, C. A., J. Stevens, K. J. Livak, P. M. Williams. 1996. Real time quantitative PCR. Genome Res. 6: 986-994. [Abstract/Free Full Text]
  43. Atasoy, U., S. L. Curry, I. López de Silanes, A. B. Shyu, V. Casolaro, M. Gorospe, C. Stellato. 2003. Regulation of eotaxin gene expression by TNF and IL-4 Through messenger RNA stabilization: involvement of the RNA-binding protein HuR. J. Immunol. 171: 4369-4378. [Abstract/Free Full Text]
  44. Alley, S. C., F. T. Ishmael, A. Jones, S. Benkovic. 2000. Mapping protein-protein interactions in the bacteriophage T4 DNA polymerase holoenzyme. J. Am. Chem. Soc. 122: 6126-6127.
  45. Ishmael, F. T., S. C. Alley, S. J. Benkovic. 2001. Identification and mapping of protein-protein interactions between gp32 and gp59 by cross-linking. J. Biol. Chem. 276: 25236-25242. [Abstract/Free Full Text]
  46. Benjamini, Y., T. Hochberg. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Soc. 57: 289-300.
  47. Thomas, P. D., M. J. Campbell, A. Kejariwal, H. Mi, B. Karlak, R. Daverman, K. Diemer, A. Muruganujan, A. Narechania. 2003. PANTHER: a library of protein families and subfamilies indexed by function. Genome Res. 13: 2129-2141. [Abstract/Free Full Text]
  48. Pullmann, R., Jr, K. Abdelmohsen, A. Lal, J. L. Martindale, R. D. Ladner, M. Gorospe. 2006. Differential stability of thymidylate synthase 3'-untranslated region polymorphic variants regulated by AUF1. J. Biol. Chem. 281: 23456-23463. [Abstract/Free Full Text]
  49. Cao, H., J. S. Tuttle, P. J. Blackshear. 2004. Immunological characterization of tristetraprolin as a low abundance, inducible, stable cytosolic protein. J. Biol. Chem. 279: 21489-21499. [Abstract/Free Full Text]
  50. Pawliczak, R., C. Logun, P. Madara, J. Barb, A. F. Suffredini, P. J. Munson, R. L. Danner, J. H. Shelhamer. 2005. Influence of IFN-{gamma} on gene expression in normal human bronchial epithelial cells: modulation of IFN-{gamma} effects by dexamethasone. Physiol. Genom. 23: 28-45. [Abstract/Free Full Text]
  51. Newton, R., N. S. Holden. 2007. Separating transrepression and transactivation: a distressing divorce for the glucocorticoid receptor?. Mol. Pharmacol. 72: 799-809. [Abstract/Free Full Text]
  52. Inoue, K., H. Takano, R. Yanagisawa, M. Sakurai, T. Ichinose, K. Sadakane, K. Hiyoshi, M. Sato, A. Shimada, M. Inoue, T. Yoshikawa. 2005. Role of metallothionein in antigen-related airway inflammation. Exp. Biol. Med. 230: 75-81. [Abstract/Free Full Text]
  53. Wesselkamper, S. C., S. A. McDowell, M. Medvedovic, T. P. Dalton, H. S. Deshmukh, M. A. Sartor, L. M. Case, L. N. Henning, M. T. Borchers, C. R. Tomlinson, et al 2006. The role of metallothionein in the pathogenesis of acute lung injury. Am. J. Respir. Cell Mol. Biol. 34: 73-82. [Abstract/Free Full Text]
  54. Stoecklin, G., S. A. Tenenbaum, T. Mayo, S. V. Chittur, A. D. George, T. E. Baroni, P. J. Blackshear, and P. Anderson. Genome-wide analysis identifies interleukin-10 mRNA as target of tristetraprolin. J. Biol. Chem. In press.
  55. Tokunaga, K., T. Shibuya, Y. Ishihama, H. Tadakuma, M. Ide, M. Yoshida, T. Funatsu, Y. Ohshima, T. Tani. 2006. Nucleocytoplasmic transport of fluorescent mRNA in living mammalian cells: nuclear mRNA export is coupled to ongoing gene transcription. Genes Cells 11: 305-317. [Abstract/Free Full Text]
  56. Dreyfuss, G., M. J. Matunis, S. Pinol-Roma, C. G. Burd. 1993. hnRNP proteins and the biogenesis of mRNA. Annu. Rev. Biochem. 62: 289-321. [Medline]
  57. Pinol-Roma, S., G. Dreyfuss. 1991. Transcription-dependent and transcription-independent nuclear transport of hnRNP proteins. Science 253: 312-314. [Abstract/Free Full Text]
  58. Pinol-Roma, S., G. Dreyfuss. 1993. hnRNP proteins: localization and transport between the nucleus and the cytoplasm. Trends Cell Biol. 3: 151-155. [Medline]
  59. Fan, X. C., J. A. Steitz. 1998. HNS, a nuclear-cytoplasmic shuttling sequence in HuR. Proc. Natl. Acad. Sci. USA 95: 15293-15298. [Abstract/Free Full Text]
  60. Lai, W. S., E. A. Kennington, P. J. Blackshear. 2002. Interactions of CCCH zinc finger proteins with mRNA: non-binding tristetraprolin mutants exert an inhibitory effect on degradation of AU-rich element-containing mRNAs. J. Biol. Chem. 277: 9606-9613. [Abstract/Free Full Text]
  61. Franks, T. M., J. Lykke-Andersen. 2007. TTP and BRF proteins nucleate processing body formation to silence mRNAs with AU-rich elements. Genes Dev. 21: 719-735. [Abstract/Free Full Text]
  62. Yang, E., E. van Nimwegen, M. Zavolan, N. Rajewsky, M. Schroeder, M. Magnasco, J. E. Darnell, Jr. 2003. Decay rates of human mRNAs: correlation with functional characteristics and sequence attributes. Genome Res. 13: 1863-1872. [Abstract/Free Full Text]
  63. Karin, M., M. Delhase. 2000. The I{kappa}B kinase (IKK) and NF-{kappa}B: key elements of proinflammatory signalling. Semin. Immunol. 12: 85-98. [Medline]
  64. Ingram, J. L., A. Antao-Menezes, J. B. Mangum, O. Lyght, P. J. Lee, J. A. Elias, J. C. Bonner. 2006. Opposing actions of Stat1 and Stat6 on IL-13-induced up-regulation of early growth response-1 and platelet-derived growth factor ligands in pulmonary fibroblasts. J. Immunol. 177: 4141-4148. [Abstract/Free Full Text]
  65. Cho, S. J., M. J. Kang, R. J. Homer, H. R. Kang, X. Zhang, P. J. Lee, J. A. Elias, C. G. Lee. 2006. Role of early growth response-1 (Egr-1) in interleukin-13-induced inflammation and remodeling. J. Biol. Chem. 281: 8161-8168. [Abstract/Free Full Text]
  66. Hass, R., M. Brach, H. Gunji, S. Kharbanda, D. Kufe. 1992. Inhibition of EGR-1 and NF-{kappa}B gene expression by dexamethasone during phorbol ester-induced human monocytic differentiation. Biochem. Pharmacol. 44: 1569-1576. [Medline]
  67. Jalonen, U., A. Lahti, R. Korhonen, H. Kankaanranta, E. Moilanen. 2005. Inhibition of tristetraprolin expression by dexamethasone in activated macrophages. Biochem. Pharmacol. 69: 733-740. [Medline]
  68. Blackshear, P. J., R. S. Phillips, J. Vazquez-Matias, H. Mohrenweiser. 2003. Polymorphisms in the genes encoding members of the tristetraprolin family of human tandem CCCH zinc finger proteins. Prog. Nucleic Acid Res. Mol. Biol. 75: 43-68. [Medline]



This article has been cited by other articles:


Home page
 J. Biol. Chem.Home page
Y. M. Schichl, U. Resch, R. Hofer-Warbinek, and R. de Martin
Tristetraprolin Impairs NF-{kappa}B/p65 Nuclear Translocation
J. Biol. Chem., October 23, 2009; 284(43): 29571 - 29581.
[Abstract] [Full Text] [PDF]

Home page
 J. Biol. Chem.Home page
J. Liang, T. Lei, Y. Song, N. Yanes, Y. Qi, and M. Fu
RNA-destabilizing Factor Tristetraprolin Negatively Regulates NF-{kappa}B Signaling
J. Biol. Chem., October 23, 2009; 284(43): 29383 - 29390.
[Abstract] [Full Text] [PDF]

Home page
 J. Pharmacol. Exp. Ther.Home page
E. M. King, M. Kaur, W. Gong, C. F. Rider, N. S. Holden, and R. Newton
Regulation of Tristetraprolin Expression by Interleukin-1{beta} and Dexamethasone in Human Pulmonary Epithelial Cells: Roles for Nuclear Factor-{kappa}B and p38 Mitogen-Activated Protein Kinase
J. Pharmacol. Exp. Ther., August 1, 2009; 330(2): 575 - 585.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Data Supplement
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ishmael, F. T.
Right arrow Articles by Stellato, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ishmael, F. T.
Right arrow Articles by Stellato, C.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS