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• W1964103615 abstract "Nitric oxide signaling is crucial for effecting long lasting changes in cells, including gene expression, cell cycle arrest, apoptosis, and differentiation. We have determined the temporal order of gene activation induced by NO in mammalian cells and have examined the signaling pathways that mediate the action of NO. Using microarrays to study the kinetics of gene activation by NO, we have determined that NO induces three distinct waves of gene activity. The first wave is induced within 30 min of exposure to NO and represents the primary gene targets of NO. It is followed by subsequent waves of gene activity that may reflect further cascades of NO-induced gene expression. We verified our results using quantitative real time PCR and further validated our conclusions about the effects of NO by using cytokines to induce endogenous NO production. We next applied pharmacological and genetic approaches to determine the signaling pathways that are used by NO to regulate gene expression. We used inhibitors of particular signaling pathways, as well as cells from animals with a deleted p53 gene, to define groups of genes that require phosphatidylinositol 3-kinase, protein kinase C, NF-κB, p53, or combinations thereof for activation by NO. Our results demonstrate that NO utilizes several independent signaling pathways to induce gene expression. Nitric oxide signaling is crucial for effecting long lasting changes in cells, including gene expression, cell cycle arrest, apoptosis, and differentiation. We have determined the temporal order of gene activation induced by NO in mammalian cells and have examined the signaling pathways that mediate the action of NO. Using microarrays to study the kinetics of gene activation by NO, we have determined that NO induces three distinct waves of gene activity. The first wave is induced within 30 min of exposure to NO and represents the primary gene targets of NO. It is followed by subsequent waves of gene activity that may reflect further cascades of NO-induced gene expression. We verified our results using quantitative real time PCR and further validated our conclusions about the effects of NO by using cytokines to induce endogenous NO production. We next applied pharmacological and genetic approaches to determine the signaling pathways that are used by NO to regulate gene expression. We used inhibitors of particular signaling pathways, as well as cells from animals with a deleted p53 gene, to define groups of genes that require phosphatidylinositol 3-kinase, protein kinase C, NF-κB, p53, or combinations thereof for activation by NO. Our results demonstrate that NO utilizes several independent signaling pathways to induce gene expression. Nitric oxide regulates a wide range of physiological responses (1Ignarro L.J. Nitric Oxide: Biology and Pathobiology. 1st ed. Academic Press, San Diego2000Google Scholar). Most of the studies of NO action in animals have focused on its activity as an effector of rapid responses, such as regulation of blood pressure, smooth muscle contraction, and neurotransmission in the central and peripheral nervous systems. In these contexts, NO action is mediated by fast acting signaling cascades, which rapidly subside after the disappearance of the original stimulus (e.g. calcium influx). NO can also stimulate signaling pathways that elicit long lasting changes in the cell, and it can also reset genetic programs. This function of NO is manifested in its ability to regulate gene expression (2Bogdan C. Trends Cell Biol. 2001; 11: 66-75Abstract Full Text Full Text PDF PubMed Scopus (456) Google Scholar), to mediate immune response and inflammation (3Nathan C. J. Clin. Investig. 2003; 111: 769-778Crossref PubMed Scopus (385) Google Scholar), and to act as an antiproliferative factor to mediate tissue differentiation and organ development (4Enikolopov G. Banerji J. Kuzin B. Cell Death Differ. 1999; 6: 956-963Crossref PubMed Scopus (80) Google Scholar, 5Peunova N. Scheinker V. Cline H. Enikolopov G. J. Neurosci. 2001; 21: 8809-8818Crossref PubMed Google Scholar). The molecular basis of these long lasting effects of NO is still unclear. To reveal the targets of NO in the cell, it will be important to understand the signaling pathways that are activated in response to NO. To investigate mechanisms underlying the long term action of NO, we used DNA microarrays to determine the temporal expression profiles of genes that respond to NO. We identified genes that are affected by NO and analyzed the temporal patterns of their expression to reveal cascades of NO-dependent gene regulation events. These results were verified by using quantitative real time PCR and validated by demonstrating that similar genes are activated in an NO-dependent manner in response to cytokines. We next used chemical inhibitors of specific signaling molecules and a mutant cell line to determine the signaling pathways that lead to the activation of specific gene targets of NO. Our results show that NO employs a variety of signaling pathways to induce gene expression; these pathways may mediate the long lasting effects of NO during cell division, tissue differentiation, response to pathogens, and disease. Cell Culture and Treatment—NIH3T3 fibroblasts were maintained at 37 °C in an atmosphere of 5% CO2 in Dulbecco's modified Eagle's medium with 10% calf serum. The fibroblasts were treated with 250 μm of the NO donor S-nitroso-N-acetylpenicillamine (SNAP 1The abbreviations used are: SNAP, S-nitroso-N-acetylpenicillamine; ODQ, 1H-(1,2,4) oxadiazolo[4,3-a]quinolxalin-1-one; PI, phosphatidylinositol; PKC, protein kinase C; MEF, mouse embryonic fibroblast; iNOS, inducible nitric-oxide synthase; l-NAME, N ω-nitro-l-arginine methyl ester hydrochloride; Q-PCR, quantitative real time PCR; HO-1, heme oxygenase-1.; Calbiochem) or 0.05% Me2SO (Sigma) for 0.5, 0.75, 1, 2, 4, 8, 12, 16, 24, and 48 h. Pharmacological inhibitors, SN50 (6 μm; Calbiochem), 1H-(1,2,4) oxadiazolo[4,3-a]quinolxalin-1-one (ODQ) (50 μm; Calbiochem), wortmannin (500 nm; Calbiochem), and calphostin (500 nm; Calbiochem), which inhibit NF-κB, soluble guanylate cyclase, PI 3-kinase, and PKC, respectively, were added to cell cultures 30 min prior to the addition of the NO donor, SNAP. The mouse embryonic fibroblasts (MEFs) from the wild type and p53-/- animals were a gift from S. Lowe (Cold Spring Harbor Laboratory). They were propagated at 37 °C and 5% CO2 in Dulbecco's modified Eagle's medium with 10% fetal calf serum. iNOS Induction—NIH3T3 cells were plated at 2 × 106 cells/35-mm dish and grown for 12 h before the addition of cytokines: tumor necrosis factor-α (10 ng/ml; R&D Systems, Minneapolis, MN), interferon-γ (200 units/ml; Calbiochem), and interleukin-1β (200 pg/ml; R&D Systems). In some experiments, iNOS activity was inhibited by the presence of 5 mm N ω-nitro-l-arginine methyl ester hydrochloride (l-NAME; Sigma), added 30 min before exposure to the cytokines. RNA Extraction and Probe Generation—Total RNA was isolated using Trizol (Invitrogen), and poly(A)+ RNA was selected with FastTrack 2.0 (Invitrogen) according to the manufacturer's protocols. A common reference was generated by combining equal portions of poly(A)+ RNA from all of the untreated control samples obtained with each time point analyzed. The probes were synthesized from poly(A)+ RNA using Superscript II RT (Invitrogen) to incorporate amine-modified nucleotides (amino allyl-dUTP; Sigma). cDNA samples were purified and concentrated using Microcon 30 spin columns (Millipore, Bedford, MA), dried, and stored at -20 °C until hybridization. Microarray Hybridization—Gene expression changes were detected by using custom printed slide arrays produced by the Cold Spring Harbor Laboratory Genome Center (intron.cshl.org/msr/). Each slide was comprised of 9,600 features, encompassing both expressed sequence tags (∼47%) and known genes (∼53%) (acquired from the NIA, National Institutes of Health, Bethesda, MD; Igsun.grc.nia.nih.gov/cDNA/cDNA.html), along with appropriate controls, such as housekeeping genes and marker genes to monitor by us predicted gene expression profiles. cDNAs of NO-inducible genes identified by us previously were incorporated into the array. For hybridization, the slides were hydrated by exposure to 1× saline sodium citrate for 1.5 min at 30 °C in a humid chamber, snap-dried on a 100 °C heating plate, rinsed in 0.1% SDS for 30 s, rinsed in distilled water for 30 s, boiled in distilled water for 5 min, then rinsed in -20 °C benzene-free ethanol, and spun dry at 2,000 × g for 5 min. cDNA samples were resuspended in buffer (0.3 m sodium bicarbonate, pH 9.0), coupled to monofunctional NHS-Cy5 or Cy3 dye (Amersham Biosciences) for 15 min at 25 °C, purified using Microcon 30 columns, and combined with mouse Cot-1 DNA (20 μg), poly(A)+ RNA (2 μg), and tRNA (2 μg). The microarrays were hybridized using GlassHyb hybridization solution (Clontech Laboratories) and washed according to the manufacturer's instructions. Hybridizations for the complete time course were performed in triplicate with color reversals for each individual time point, resulting in a total of six replicates/time point. To minimize variability, all of the samples from each experimental treatment were simultaneously hybridized, washed, and scanned. Microarray Image Analysis—The microarray slides were scanned using GenePix scanner and software (version 3.0; Axon Instruments, Inc., Foster City, CA). Fluorescence intensities for all spots were exported to the data analysis software, GeneSpring 4.2 (Silicon Genetics, Redwood City, CA) and normalized by the “per chip normalization” method. Expression ratio values obtained from the six independent replicates were averaged for each experimental time point and filtered for changes that were statistically significant (p < 0.05, compared with reference by Student's t test for each time point) and either up-regulated or down-regulated 1.3-fold. Expression profiles of the filtered data set were further analyzed for coordinated expression patterns and functional information by using the hierarchical clustering program in the GeneSpring program suite. Functional annotation was performed by searching NCBI Protein Database and SOURCE database (source.stanford.edu). Real Time Quantitative PCR—Total RNA (2 μg) was reverse transcribed into cDNA using the Taqman probe kit (Applied Biosystems) following the manufacturer's instructions. Primers for selected genes were designed via the Primer Express software (version 1.0; PE Applied Biosystems) and are listed in Table 1 of the supplemental material. Quantitative real time PCR (Q-PCR) included the following: diluted cDNA sample, 0.5 μmol/liter primers, nucleotides, Taq DNA polymerase, and buffer included in the SYBR Green I Mastermix (PE Applied Biosystems). Using the ABI Prism 7700 sequence detection system (PE Applied Biosystems), PCR cycling conditions were as follows: 50 °C for 2 min, 95 °C for 10 min, 40 cycles at 94 °C for 15 s, and 60 °C for 1 min. Sequence Detector Software (version 1.6.3; PE Applied Biosystems) was used to extract the PCR data, which were then exported to Excel (Microsoft, Redmond, WA) for further analysis. Expression of target genes were measured in triplicate and were normalized to β-actin expression levels. Western Blot Analysis—Following exposure to a cytokine mixture, the cells were harvested on ice and resuspended in 0.2 ml of lysis buffer (10 mm Tris-HCl, pH 7.5, 1 mm EDTA, 400 mm NaCl, 10% glycerol, 0.5% Nonidet P-40, 1 mm dithiothreitol, 1 mm phenylmethylsulfonyl fluoride, 1 μg/ml aprotinin, 1 μg/ml leupeptin, and 1 μg/ml pepstatin) for 25 min. Following a 30-min spin at 14,000 rpm, the supernatant was collected. Protein concentration was determined using the BCA protein assay reagent (Pierce), and all of the samples were normalized by diluting with the lysis buffer. The protein samples were mixed with the sample buffer (125 mm Tris-HCl, pH 6.8, 4% SDS, 20% glycerol, 0.01% bromphenol blue, and 100 mm 2-mercaptoethanol), boiled for 5 min, and loaded onto a 7.5% SDS-polyacrylamide gel. Separated proteins were transferred from the gel to Immobilon P membrane (Millipore) by semi-dry blotting. The membrane was washed with phosphate-buffered saline and blocked overnight in phosphate-buffered saline with 5% dry milk. The membranes were incubated with antibodies to iNOS (1:2000; N32030; Transduction Labs) and β-actin (1:2000; A-5441; Sigma) followed by anti-mouse antibody conjugated to horseradish peroxidase and the signal was detected using chemiluminescent substrate for horseradish peroxidase (Supersignal West Femto Maximum Sensitivity Substrate; Pierce) and Hyperfilm (Amersham Biosciences). Measurements of NOS Activity in Cellular Extracts—The cell extracts were prepared from NIH3T3 fibroblasts at 4, 12, 16, 24, and 30 h after the addition of the cytokines, as well as from untreated cells. The extracts were prepared as follows. The cells were washed with phosphate-buffered saline, pH 7.4, resuspended in extraction buffer (20 mm HEPES, pH 7.4, 1 μg/ml aprotinin, 1 μg/ml leupeptin, 1 μg/ml pepstatin, and 1 mm phenylmethylsulfonyl fluoride), and subjected to six rounds of freezing and thawing. After centrifugation for 15 min at 14,000 rpm, the supernatants were collected and used for the NOS assay as described (6Bredt D.S. Snyder S.H. Proc. Natl. Acad. Sci. U. S. A. 1990; 87: 682-685Crossref PubMed Scopus (3121) Google Scholar). NOS assay reactions contained 50 mm HEPES, pH 7.4, 2 mm CaCl2, 2.5 μml-arginine, 1 mm NADPH, 20 μm tetrahydro-l-biopterin, 10 μg/ml calmodulin, 2 μl of l-[3H]arginine (2.29 terabecquerel/mmol, 62.0 Ci/mmol) (Amersham Biosciences) and 50 μl (100-150 μg/ml) of a soluble protein extract in a 150-μl reaction mixture. All of the reactions were incubated at 25 °C for 30 min and then processed to assess the amount of [3H]arginine converted to [3H]citrulline. The BCA reagent system (Pierce) was used to determine the protein concentration in the extracts, and the results were used to normalize the arginine-citrulline conversion assays. Temporal Patterns of Gene Activation in Response to NO—To identify the gene targets of NO, we determined the temporal gene expression profile of cells exposed to NO by using cDNA microarrays. We used NIH3T3 cells as a test cell line; these are well characterized cells that have served for many years as a standard for biochemical and genetic experiments. To produce NO, we used an NO donor compound SNAP whose chemical and pharmacological properties have been thoroughly described (1Ignarro L.J. Nitric Oxide: Biology and Pathobiology. 1st ed. Academic Press, San Diego2000Google Scholar, 7Wang P.G. Xian M. Tang X. Wu X. Wen Z. Cai T. Janczuk A.J. Chem. Rev. 2002; 102: 1091-1134Crossref PubMed Scopus (1093) Google Scholar). An additional consideration for choosing a well characterized fibroblast line and a well studied donor of NO was to establish a “base-line” data base that will assist in future studies describing gene activation by NO and dissecting the signaling pathways in specialized cell types. We added NO donor SNAP (250 μm) to exponentially growing NIH3T3 cells, harvested the cells at 0.5, 0.75, 1, 2, 4, 8, 12, 16, 24, and 48 h, and isolated the RNA (Fig. 1A). This concentration of SNAP was determined to induce cell cycle arrest; this arrest was followed by renewed cell division ∼40 h after the addition of the chemical (data not shown). Importantly, even higher concentrations of SNAP (>500 μm) did not induce detectable cell death (data not shown). The time points were chosen to identify (a) the very early responses of cells to NO, which reflect activation of immediate gene targets; (b) the intermediate and long term responses that may reflect multiple cascades of gene activation triggered by NO; and (c) the late responses when the levels of NO have decreased enough for the cells to resume division. cDNAs prepared from SNAP-treated samples and the corresponding controls were labeled with either Cy5 or Cy3 and hybridized to microarrays containing ∼10,000 cDNA probes, (further supplemented with NO-induced target genes that we had previously identified in independent experiments (8Nakaya N. Lowe S.W. Taya Y. Chenchik A. Enikolopov G. Oncogene. 2000; 19: 6369-6375Crossref PubMed Scopus (59) Google Scholar). 2N. Nakaya, J. Hemish, and G. Enikolopov, unpublished data. Each comparison was performed in triplicate with reciprocal labeling (color reversals); thus, each time point is a result of at least six independent measurements. After normalizing and averaging the replicate hybridizations for each time point, the data set was analyzed for genes that were up-regulated and down-regulated more than 1.3-fold in a statistically significant manner (p < 0.05). Approximately 560 genes were selected (gene identities and associated changes in mRNA levels are provided in Table 2 of the supplemental material) and further analyzed by hierarchical clustering to reveal sets of genes that share expression patterns over the examined time points (Fig. 1B). The dendrogram reveals clusters of genes whose expression patterns changed in a similar manner after exposure to NO. A summary of the changes evoked by NO is presented by histograms (Fig. 1C), which show the number of genes activated by NO at each time point. Three distinct waves of gene induction were observed (see Table 2 of the supplemental material for genes included in groups I, II, and III). The first group of genes (group I) is induced very rapidly, as early as 30 min after exposure to the NO donor; these genes may belong to the class of immediate-early genes that do not require protein synthesis for activation. The second group (group II) is induced 4 h following the addition of the NO donor. This group may include genes that require production of new proteins for their activation. Because some of the genes in group I code for transcription factors (e.g. c-fos and egr-1), it is likely that some of the genes in group II correspond to the transcriptional targets of the factors belonging to group I. Finally, a large number of genes (group III) is activated 12 h after the addition of SNAP. These genes may include the targets of group II genes as well as genes whose expression reflects the cell cycle arrest at that time point. Interestingly, not only the number of up-regulated genes but also the magnitude of change in the expression levels was greater for genes in group III compared with genes in groups I and II. Together, these data clearly show that there are distinct temporal cascades of gene activation events induced by NO. A large number of the NO-regulated genes were binned into categories based on functional annotation (as determined by the NCBI Protein Database and SOURCE). These genes are involved in signaling (3% of the analyzed genes), metabolism (7%), cell cycle (3%), stress response (1%), transcription (6%), protein degradation (3%), iron homeostasis (1%), adhesion (2%), as well as transport, apoptosis, and formation of the cytoskeleton (Fig. 2A). The remaining genes are present as expressed sequence tags in the collection of the tested genes (54% of the genes analyzed by temporal clustering). Examples of genes assigned to the functional categories are provided in Fig. 1 of the supplemental material. A wide range of functional groups revealed by this classification suggests that NO has a broad impact on cell physiology, affecting genes involved in a variety of biochemical pathways and diverse cellular functions. We next examined the temporal profile of the changes within the functional categories (Fig. 1 of the supplemental material and Fig. 2B). Although in some functional groups the majority of genes changed their expression in a coordinated manner (e.g. stress response genes), genes in other groups showed few signs of coordinated changes (e.g. genes related to cell cycle or iron regulation). Our results show that NO-inducible genes can be grouped into distinct clusters based on similar changes in expression pattern; these clusters may represent targets of the same NO-activated signaling pathways. At the same time, the diversity of the expression patterns indicates that NO activates a complex cascade of signaling events. Verification of the Identified Changes—We sought to confirm the changes in selected candidate transcripts levels identified by the micorarray experiments by using Q-PCR. The same RNA samples used for the microarray experiments were used in Q-PCR to analyze three groups of genes: those induced early (within 30 min) after addition of the NO donor (egr-1, gly96, c-myc, and c-fos), those induced after 2-4 h (heme oxygenase-1 (HO-1), thioredoxin reductase, BNIP3, and transferrin receptor), and those induced 8-12 h after the addition of the donor (cyclin G, mdm2, nidogen 1, and p21Cip1) (Fig. 3). These results show a good correlation between the kinetics of changes demonstrated by the two methods. Interestingly, Q-PCR also revealed some subtle features of the response patterns that were not apparent from the microarray analysis. For instance, a number of the immediate-early genes (egr-1, gly96, c-myc, and c-fos) showed a biphasic pattern of expression; a very rapid response (within 30 min after addition of the NO donor) was later accompanied by a second wave of increase in RNA levels. This second increase started 2-4 h after the initial exposure to NO and may represent protein synthesis-dependent changes in the expression of these genes. Validation of the Identified Changes—We have demonstrated that the NO-induced changes identified using microarrays can be confirmed using an alternative approach. We next sought to validate the identified targets of NO by comparing the changes generated by exposure to an external source of NO (SNAP) with the changes induced by NO that is enzymatically produced by NO synthases in the cells in vivo. To this end, we stimulated expression of the iNOS and production of endogenous NO by treating NIH3T3 cells with a mixture of cytokines (tumor necrosis factor-α, interferon-γ, and interleukin-1β). This mixture is known as a potent inducer of iNOS gene expression in a variety of cells (1Ignarro L.J. Nitric Oxide: Biology and Pathobiology. 1st ed. Academic Press, San Diego2000Google Scholar, 9Bredt D.S. Snyder S.H. Annu. Rev. Biochem. 1994; 63: 175-195Crossref PubMed Scopus (2132) Google Scholar, 10Alderton W.K. Cooper C.E. Knowles R.G. Biochem. J. 2001; 357: 593-615Crossref PubMed Scopus (3257) Google Scholar). Expression of iNOS protein was clearly seen on the Western blots 12 h after the addition of the cytokines (Fig. 4A), with or without a specific NOS inhibitor l-NAME. Analysis of iNOS RNA using Q-PCR confirmed that there was a strong response to the addition of the cytokine mixture (Fig. 4B). Finally, we confirmed the induction of iNOS by measuring its enzymatic activity, which strongly increased over time from the undetectable levels in unstimulated cells (Fig. 4C). We next examined whether the cytokine-mediated induction of iNOS also induced the expression of genes that we had identified previously. We used Q-PCR to determine the changes invoked by the cytokines on NO-inducible genes identified in the microarray screen. We also evaluated the contribution of NO to cytokine action on gene expression by adding a NOS inhibitor (l-NAME) along with the cytokines. Examples of the changes induced by the cytokines are shown in Fig. 4D. Expression of HO-1 gene was strongly induced by the cytokines and gradually increased from 4 to 30 h after the addition of the cytokines. Expression of mdm2 was also strongly induced by the cytokines and was further augmented after 24 h of treatment. The addition of NOS inhibitor strongly reduced the response for both cases; this was particularly apparent at the later time points. This suggests that the largest component of the response of HO-1 and mdm2 to the cytokines is NO-dependent. However, it also suggests that a small part of the response, particularly at the earlier time points, may be independent of NO production and may reflect gene activation by NO-independent pathways. Fig. 4D also presents examples of genes (BNIP3 and gly96) whose activation by cytokines is less dependent on NO than that of HO-1 and mdm2. In this case a large part of the response cannot be eliminated by the addition of the NOS inhibitor, indicating that for these genes the NO signal mediates only a small part of the response to the cytokines. For all of the genes tested in this series of experiments, incubation with NOS inhibitors alone (in the absence of the cytokines) does not change their expression (data not shown). Importantly, in each case tested, those genes that have been previously identified as inducible by the NO donor were also induced by the addition of the cytokines, and at least part of that response was dependent on NO. These data suggest that endogenously produced NO activates a set of genes similar to that activated by the exogenously added NO and further validates the gene targets of NO we have identified. Signaling Pathways Employed by NO to Activate Gene Expression—We next sought to determine the signaling pathways that mediate the action of NO on gene expression by using pharmacological and genetic approaches. In a pharmacological approach, we exposed the cells to NO in the presence of selective inhibitors of specific signaling pathways: wortmannin, which inhibits PI 3-kinase-mediated signaling; calphostin, which inhibits PKC signaling; SN50, which inhibits NF-κB action; and ODQ, which inhibits soluble guanylate cyclase. Additionally, we used a genetic approach to compare the response to NO in normal cells and in cells lacking the tumor suppressor gene p53 (which has been implicated in the action of NO in several settings) (8Nakaya N. Lowe S.W. Taya Y. Chenchik A. Enikolopov G. Oncogene. 2000; 19: 6369-6375Crossref PubMed Scopus (59) Google Scholar, 11Forrester K. Ambs S. Lupold S.E. Kapust R.B. Spillare E.A. Weinberg W.C. Felley-Bosco E. Wang X.W. Geller D.A. Tzeng E. Billiar T.R. Harris C.C. Proc. Natl. Acad. Sci. U. S. A. 1996; 93: 2442-2447Crossref PubMed Scopus (391) Google Scholar, 12Messmer U.K. Brune B. Biochem. J. 1996; 319: 299-305Crossref PubMed Scopus (271) Google Scholar, 13Brune B. von Knethen A. Sandau K.B. Eur. J. Pharmacol. 1998; 351: 261-272Crossref PubMed Scopus (389) Google Scholar, 14Wang X. Zalcenstein A. Oren M. Cell Death Differ. 2003; 10: 468-476Crossref PubMed Scopus (88) Google Scholar). For this series of experiments, we used Q-PCR on a subset of NO-inducible genes, because we expected that in some cases only a part of the response may be affected by the inhibitors and because this technique is more likely to reveal subtle changes. The data for these experiments (each data point determined by at least three independent measurements) are summarized in Table I.Table IEffect of signaling pathway blockades on NO-stimulated gene expression in NIH3T3 fibroblastsGene nameAccessionUntreatedWortmanninCalphostinUntreatedSN50UntreatedODQWT MEFP53−/− MEFIMAGE 524571A115736012.27 ± 1.485.36 ± 0.31ap < 0.01 compared with reference using Student's t test.8.24 ± 0.82bp < 0.05 compared with reference using Student's t test.7.59 ± 0.806.30 ± 0.7710.51 ± 1.557.50 ± 1.084.15 ± 0.602.01 ± 0.38ap < 0.01 compared with reference using Student's t test.mdm2X588768.81 ± 0.603.45 ± 0.52ap < 0.01 compared with reference using Student's t test.6.82 ± 1.057.70 ± 0.516.13 ± 0.579.14 ± 1.318.35 ± 1.484.57 ± 0.841.12 ± 0.11bp < 0.05 compared with reference using Student's t test.p21/WAF1U0950711.49 ± 1.476.89 ± 0.61ap < 0.01 compared with reference using Student's t test.7.67 ± 0.66bp < 0.05 compared with reference using Student's t test.5.69 ± 0.525.51 ± 0.598.19 ± 0.6510.76 ± 1.502.45 ± 0.061.23 ± 0.46bp < 0.05 compared with reference using Student's t test.gadd45L281778.11 ± 0.624.69 ± 0.83ap < 0.01 compared with reference using Student's t test.6.85 ± 0.784.79 ± 0.433.91 ± 0.727.70 ± 0.634.55 ± 0.61ap < 0.01 compared with reference using Student's t test.1.87 ± 0.161.46 ± 0.03cycGZ371106.15 ± 0.665.44 ± 0.615.53 ± 0.745.51 ± 0.566.76 ± 0.725.73 ± 0.424.80 ± 1.151.74 ± 0.221.14 ± 0.25reprimoAB043586NDNDNDNDND4.92 ± 1.569.06 ± 6.244.20 ± 0.281.43 ± 0.12ap < 0.01 compared with reference using Student's t test.transferrin receptorX573496.10 ± 0.453.47 ± 0.30ap < 0.01 compared with reference using Student's t test.3.39 ± 0.24ap < 0.01 compared with reference using Student's t test.6.91 ± 1.134.62 ± 0.384.49 ± 0.814.52 ± 0.622.66 ± 0.223.81 ± 0.72c-mycX010233.22 ± 0.212.95 ± 0.462.84 ± 0.48NDND3.43 ± 0.382.12 ± 0.25NDNDbaxL224723.05 ± 0.403.30 ± 0.373.58 ± 0.503.64 ± 0.422.05 ± 0.25ap < 0.01 compared with reference using Student's t test.3.35 ± 0.464.33 ± 0.601.95 ± 0.261.49 ± 0.06ornithine decarboxylaseM106242.21 ± 0.171.95 ± 0.213.21 ± 0.303.19 ± 0.102.58 ± 0.273.14 ± 0.321.50 ± 0.22ap < 0.01 compared with reference using Student's t test.NDNDmcp3S712514.39 ± 0.902.20 ± 0.30bp < 0.05 compared with reference using Student's t test.2.71 ± 0.561.89 ± 0.211.34 ± 0.133.09 ± 0.382.11 ± 0.67NDNDIMAGE 334547W184093.30 ± 0.532.61 ± 0.273.88 ± 0.54NDND2.97 ± 0.382.17 ± 0.39NDNDpRBM263913.16 ± 0.761.93 ± 0.131.91 ± 0.21NDND2.89 ± 0.702.29 ± 0.361.79 ± 0.201.74 ± 0.73Bcl-XLL350492.66 ± 0.115.12 ± 0.72ap < 0.01 compared with reference using Student's t test.3.11 ± 0.623.83 ± 0.382.36 ± 0.21ap < 0.01 compared with reference using Student's t test.2.83 ± 0.542.74 ± 0.432.11 ± 0.762.06 ± 0.80gly96X676443.26 ± 0.435.26 ± 0.64bp < 0.05 compared with reference using Student's t test.5.17 ± 0.962.08 ± 0.121.54 ± 0.07ap < 0.01 compared with reference using Student's t test.2.76 ± 0.163.06 ± 0.332.31 ± 0.242.14 ± 0.28Protein kinase ζ zeta-interacting proteinNM_0110182.71 ± 0.280.91 ± 0.08ap < 0.01 compared with reference using Student's t test.2.07 ±" @default.
• W1964103615 created "2016-06-24" @default.
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• W1964103615 creator A5048257604 @default.
• W1964103615 creator A5050670637 @default.
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• W1964103615 date "2003-10-01" @default.
• W1964103615 modified "2023-10-18" @default.
• W1964103615 title "Nitric Oxide Activates Diverse Signaling Pathways to Regulate Gene Expression" @default.
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