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Molecular and Cellular Biology, May 2006, p. 3492-3504, Vol. 26, No. 9
0270-7306/06/$08.00+0 doi:10.1128/MCB.26.9.3492-3504.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
Division of Radiation and Cancer Biology, Department of Radiation Oncology,1 Department of Genetics, Center for Clinical Sciences Research, Department of Radiation Oncology, Stanford University, Stanford, California 94303-51522
Received 28 June 2005/ Returned for modification 15 September 2005/ Accepted 2 February 2006
| ABSTRACT |
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| INTRODUCTION |
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Few rigorous genetic analyses have been undertaken to address the mechanism of p53-dependent apoptosis in response to hypoxia. Hypoxia-induced apoptosis has been shown to be dependent on p53, Apaf 1, caspase 9, and caspase 3, indicating that the mitochondrial apoptosis pathway plays a significant role in this form of death (43). In contrast, previous studies have indicated that Bax is not required for p53-dependent hypoxia-induced apoptosis (2). Therefore, we used transformed mouse embryonic fibroblasts (MEFs) that undergo rapid hypoxia-induced apoptosis and hypoxia-regulated p53 human tumor cells to investigate the mechanism of p53-signaled apoptosis. We focused on transformed MEFs to study the role of p53 in hypoxia, and in particular hypoxia-induced apoptosis, as these cells undergo apoptosis rapidly when only oxygen is decreased in the environment and do not require the removal of glucose or serum like other cell systems (22, 33). We used, among other techniques, extensive DNA microarray expression profiling and mutation analysis to determine whether hypoxia-induced p53 is nuclear and whether its transrepressor activity is necessary and sufficient to induce apoptosis under hypoxic conditions in both mouse and human systems. Most importantly, we also investigated whether mutations in p53 that abolish transrepression activity inhibit apoptosis in response to hypoxia.
| MATERIALS AND METHODS |
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Mutagenesis. Mutants were generated using the Quick Change mutagenesis kit (Stratagene). All mutants were fully sequenced before use to ensure no nonspecific mutations had been generated during the procedure.
Hypoxia treatment. Cells were plated in glass dishes, and treatment was carried out in a hypoxia chamber (<0.02% O2; Sheldon Corp., Cornelius, Oreg.) or in a mixed-gas incubator (2% O2).
Immunoblotting.
For immunoblotting, cells were lysed in 9 M urea, 75 mM Tris-HCl, pH 7.5, and 0.15 M ß-mercaptoethanol and sonicated briefly. Protein (50 µg) was electrophoresed on 7.5% polyacrylamide gels. The antibodies used in this study were as follows: p53 ser 15 (16G8 monoclonal no. 9286; Cell Signaling), MDM2 (SMP-14; Santa Cruz), CM-5 (Vector Laboratories), glyceraldehyde-3-phosphate dehydrogenase (GAPDH; TRK5G4-6C5; Research Diagnostics), p53-DO-1 (Santa Cruz), HIF-1
(H72320; Transduction Laboratories), tubulin (Research Diagnostics), CBP (Santa Cruz), and p53-FL393R (Santa Cruz).
RNA isolation and Northern hybridization. Total RNA was isolated from 106 to 107 cells grown in monolayers with Trizol reagent (Gibco BRL) according to the manufacturer's protocol. Northern hybridization assays were performed using 5 µg of total RNA. Radiolabeled probes were synthesized with a random-priming kit (Gibco BRL) from DNA fragments obtained by PCR amplification of mouse or human cDNA and gel purification of the DNA product.
qRT-PCR. For selective microarray confirmation, we performed quantitative real-time PCR (qRT-PCR). We obtained cDNA by reverse transcription of 1 µg of DNase-treated total RNA from each sample using random hexamer priming in 50-µl reactions according to the manufacturer's recommendations (Taqman reverse transcription reagent kit; Applied Biosystems, Foster City, CA). We proceeded with qRT-PCR using the Applied Biosystems Prism 7900HT sequence detection system. A nonmultiplexed SYBR Green assay in which each cDNA sample was evaluated at least in triplicate 20-µl reactions was used for all target transcripts. Expression values were normalized to the 18s rRNA. qRT-PCR primers were designed using Primer Express version 2.0.0 (Applied Biosystems) and tested to confirm the appropriate product size and optimal concentrations. All primer sequences are available upon request.
Determination of apoptotic cells. Cells with apoptotic morphology were identified by staining them with Hoechst dye 33342 (5 µg/ml) for changes in nuclear characteristics and with propidium iodide (5 µg/ml) for loss of membrane integrity. Apoptotic values were calculated as the percentage of apoptotic cells relative to the total number of cells in each field (>100 cells) and represent the average of 16 randomly selected fields per 60-mm dish.
ChIP. Chromatin immunoprecipitation (ChIP) assays were performed as described previously with the following modification (24). Fixed cells were sonicated 12 times for 10 seconds per pulse at maximum setting using a Sonics Vibracell 130 equipped with a 3-mm microtip. The antibodies used for immunoprecipitation were anti-phosphoserine 15 p53 (Cell Signaling), mouse p53 CM-5 (Vector Laboratories), and CBP (Santa Cruz). Primer sequences were as follows: mouse Perp, 5' TGAATGTTTGGCTTATATTTGTGGAG and 3' CCTTCTTTCAGTGCATACCTCATCCC; mouse Ankyrin-like repeat protein, 5' CCCCTTCACTCTCCTCTTTC and 3' GTGCGTCTGAGGCTGGAGAC; and mouse Cdc25C, 5' GGGGCGAGAGAATTTAGTAC and 3' CCGGAGATGGCCTGAAGGC. All other primer sequences and conditions are available upon request. For quantitation, serial dilutions of inputs were used to quantify the intensities of bands generated by PCR and separated on an agarose gel.
Preparation and hybridization of microarrays. Mouse genome MGU74Av2 GeneChip arrays (Affymetrix, Santa Clara, CA) were used for mRNA expression profiling. The preparation of samples and hybridization were carried out essentially as described by Affymetrix. Total RNA was prepared using Trizol (Invitrogen). The raw-image DAT data files were initially processed using Affymetrix GeneChip software (version 5) to create CEL files.
Statistical analysis of microarrays. Higher-level analysis of microarray CEL files was performed using dChip v. 1.3 (28). Intensity levels of array images were normalized using invariant set normalization, and expression values were computed using the model-based expression value method (positive-match-only model) (27). Inter- and intra-array outliers were detected as previously described, and samples with >5% inter- or intra-array outliers were discarded. Array images were visually inspected, and samples with salient image contamination were also discarded, leaving four to six replicates per condition. Normalized probe levels and model-based expression values were recomputed with the remaining arrays, and expression values were log transformed (base 2). Log transforming the data yielded a compressed dynamic range of changes that were more normally distributed, making them more easily interpretable in both directions.
Gene lists comparing expression levels between conditions were generated. The lists were filtered to contain genes with positive calls of >20% and log-transformed changes of >1.0 (equivalent to a 2.0-fold induction or repression in untransformed values). Unpaired t tests were used to ensure that gene expression changes were statistically significant across replicates (P value
0.05), and genes failing the t test were excluded from the lists. p53 dependence across two conditions was computed from the difference of differences in log-transformed means between wild-type p53 and p53 null samples. This is more precisely defined as follows. Let x+ be the log-transformed mean of condition x for the wild-type p53 samples, and let x be the log-transformed mean for the p53 null samples. The p53-dependent induction level between two conditions, a and b, is then computed as (a+ b+) (a b), and the p53-dependent repression level is computed as (a b) (a+ b+).
Unsupervised hierarchical clusters of arrays were also generated. Lists of the 45 genes showing the greatest cross-conditional effects in each comparison were used for clustering. Distance values between two given genes were computed as 1 r, where r is the Pearson correlation coefficient between the standardized expression values of the two genes. Expression values of newly formed cluster branches were calculated as the average difference between the centroids of their subbranches across all samples.
| RESULTS |
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We analyzed these array data for genes induced in a p53-dependent manner in response to either the DNA-damaging agent adriamycin or hypoxia. The list of genes induced by adriamycin contained many genes previously identified to be p53 targets involved in cell cycle regulation and apoptosis, for example, Perp and Apaf-1. Interestingly, of all the genes induced by adriamycin treatment, 92% were induced in a p53-dependent manner (Fig. 2; see Fig. S1 in the supplemental material). In contrast, the list of genes induced by p53 in response to hypoxia did not contain any genes previously known to induce apoptosis or cell cycle arrest in a p53-dependent manner, except p21 (see Fig. S1 in the supplemental material). In particular, the levels of the proapoptotic genes Noxa, Perp, Bax, and Puma were not elevated in response to hypoxia, or their expression was low and unchanged. We further investigated genes that appeared to be induced in a p53-dependent manner in response to hypoxia by Northern blotting and qRT-PCR (see Fig. S2 in the supplemental material). Of the genes analyzed, none were induced by hypoxia in a p53-dependent manner. In fact, these genes scored as inducible because their expression was maintained under hypoxia in a p53-dependent manner. For example, both Dusp 6 and Myc showed reduced mRNA levels in hypoxia in the absence of p53, indicating that hypoxic-p53 had led to increased message stability. When the two stresses, adriamycin and hypoxia, were compared, only seven genes were found that were induced in a p53-dependent manner in both cases, demonstrating the diverse transcriptional responses to these different stresses. Of these seven genes, none had a previously characterized role in apoptosis, the cell cycle, or DNA repair.
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is present, for example, in response to hypoxia or hypoxia mimetics, such as desferrioxamine and CoCl2. All mutant constructs were validated by Western blotting to ensure expression of full-length p53 in response to hypoxia (Fig. 6B). The immunoblot shows that the p53 proteins are expressed at very low levels during incubation under normal conditions but are induced robustly in response to hypoxia. To investigate the cellular localization of these mutants, H1299 cells were transfected with the HRE-driven p53 constructs and treated with desferrioxamine or hypoxia to induce HRE-regulated p53 expression. The cells were then fixed and stained for
-tubulin (green) and p53 (red). The localizations of 5x HRE mp53wt, 5x HRE mp5325,26, and 5x HRE mp53P/A are shown in Fig. 6C. In each case, all of the mutants were found to be exclusively localized to the nucleus. This is unsurprising in the case of the p5325,26 and p5325,26,53,53 mutants, which would not be able to leave the nucleus, as they fail to bind mdm2 (29). We also assessed the abilities of some of the mutants to bind DNA. myc/ras-transformed p53/ MEFs were transfected with 5x HRE mp53wt, 5x HRE mp5325,26, and 5x HRE mp5325,26,53,54; exposed to 2% O2 to express p53; and analyzed by ChIP (Fig. 6D). Under mild hypoxia, p53wt binds well to a repressed promoter (Ankyrin-like repeat protein) and two activated promoters involved in apoptosis and cell cycle arrest (Apaf-1 and p21, respectively). Surprisingly, both p5325,26 and p5325,26,53,54 mutants demonstrated promoter-specific binding. In the case of the Ankyrin-like repeat protein, all of the p53 forms bound with approximately the same ability (binding approximately 0.0016% of the input). However, in the case of both the Apaf-1 and p21 promoters, both the 25-26 and 25-26-53-54 mutants bound approximately four to eight times more weakly than the wild type (0.0065% and 0.026%, respectively). There was little if any binding of wild-type p53 under normoxic conditions (Fig. 6D). The DNA-binding mutant (p53245) had insignificant binding (data not shown). These results demonstrate that the various forms of p53 can bind DNA, although with reduced ability on some promoters. One of the many benefits of this system is the ability to express p53 only during hypoxia, eliminating the transcriptional effects of p53 that occur under normal conditions, as observed from our microarray data.
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pro mutant) reduced the level of transrepression by approximately 40%, while the mutation of the individual prolines (the P/A mutant) had no effect on repression levels. Similar results were also found with human p53 constructs, as well as with the survivin reporter construct (data not shown).
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pro and DNA-binding (residue 245) mutants, which are also defective in transrepression, were also significantly compromised in the ability to induce apoptosis. Taken together, these results indicate that mutations impacting p53 transrepression significantly diminish p53-dependent apoptosis under hypoxic conditions and that the 25-26 and 53-54 domains work in the same pathway in regulating gene repression and apoptosis. These studies have uncovered a previously unknown role for the 53-54 domain in transrepression and apoptosis.
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| DISCUSSION |
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pro) abolished the transactivation potential of p53. One concern with the removal of such a large number of amino acids in the polyproline region, as in the
pro mutant, is the generation of an inert protein that has little biologic activity of any kind. Interestingly, mutation of the individual proline residues within the proline-rich region showed that they are not required for p53-mediated transrepression or apoptosis. Our detailed mutation analysis also revealed that DNA-binding mutants (residues 245 in the mouse and 175 in humans) are unable to repress the Runx 2 promoter or induce apoptosis. Despite these conclusions, we were unable to demonstrate by ChIP the direct binding of p53 to the Runx 2 promoter. Our search for p53 binding sites in the Runx 2 gene was limited to 2.8 kb upstream of the transcriptional start site, as that is the region of the promoter present in the Runx 2 reporter construct used in our repression assays. It is, however, possible that p53 represses the Runx 2 promoter via an indirect mechanism. In such a scenario, p53 would repress a gene product which would then have a transcriptional effect on Runx 2. The Bmp 2 gene is such a candidate, as it is upstream of Runx 2 in the bone differentiation pathway and has an identified p53 binding site in the gene promoter. It should also be considered that p53 associated with hypoxia-repressed target genes may be modified or complexed in such a way as to make immunoprecipitation difficult with the antibodies and under the conditions used. One of the most striking findings from this study is the difference between the p53-mediated responses to genotoxic stress and nongenotoxic stress in oncogenically transformed cells. In contrast to DNA damage, hypoxia fails to induce endogenous downstream p53 effector mRNAs and proteins. While DNA damage induces the differential interaction of p53 with the transcriptional activator p300 or the transcriptional corepressor mSin3A, hypoxia primarily induces an interaction of p53 with mSin3A, but not with p300 (23). We propose the following model for the transcriptional role of p53 in response to different stresses, illustrated in Fig. 9. Our extensive microarray data demonstrated that in the presence of normoxic or oncogene-mediated stress, p53 has a significant transcriptional presence. This included the activation of known p53 target genes with canonical binding sites, such as p21, as well as repression of many targets, including the previously unidentified Ankyrin-like repeat protein. Under these conditions, p53 is situated on the promoters of both repressed and activated genes. Further studies will determine if p53-mediated repression of these promoters is through interference with the binding of other transcription factor-coactivator complexes within the promoter. It is noteworthy that the p53 binding site identified in the Ankyrin-like repeat protein gene promoter does not overlap with either an Sp1 site or a GC region, as observed in the Cdc25C gene promoter (44). DNA damage-induced p53 can also be associated with both activated and repressed genes (Cdc25C). However, our microarray analysis indicates that adriamycin-induced p53 has little or no repressive activity. Our findings demonstrating the rapid switch from transcriptional inertia to competency during reoxygenation also suggest that there is a damage signal which recruits coactivator molecules to p53. During hypoxia, p53 is still able to associate with the promoters of activated genes, something we have demonstrated for Perp, Apaf 1, p21, and mdm2 (Fig. 1 and data not shown), but an additional signal is required for recruitment or interaction with coactivators. Another possibility is that cofactors may be blocked from interacting with p53, rendering p53 inert. During hypoxia, p53 is also able to associate with genes which can be repressed in a p53-dependent manner, for example, Ankyrin-like repeat protein and Cdc25C, although this association can have little or no effect. We predict that specific targets repressed by hypoxia-induced p53 promoter binding exist but have not yet been identified. Further studies using ChIP-on-ChIP technologies will aid in the identification of such targets. An alternative mechanism that we propose here is that hypoxia-induced p53-mediated repression can occur in the absence of direct binding to gene promoters. Repression independent of p53 binding to DNA has been proposed as a result of interactions with the TATA-binding protein (14, 41). More recently, St. Clair et al. demonstrated that p53 could repress the Cdc25C promoter through the CDE/CHR elements and that this was not mediated through direct binding (44). A recent genome-wide analysis of p53 binding sites determined that there was no enrichment for p53 binding sites in genes previously identified as p53-repressed targets. This analysis was restricted to the identification of p53 binding sites with the minimal spacing between two canonical half-sites and has yet to be expanded to include all p53 binding sites (30). It is also possible that p53 represses by directly acting on an intermediate subset of gene promoters, which then have more broad repressive effects on other promoters.
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, which has evolved to work specifically at low oxygen concentrations and which has many targets, may compete p300 away from p53 (40). However, we have found that in the absence of HIF, p53 still does not regain transcriptional activity. It should be noted that more and more genes are being identified that are repressed by hypoxia independently of p53 status (7, 8). Another hypothesis is that hypoxia-induced p53 is modified or fails to be modified in a manner that prevents interactions with transcriptional coactivators. In addition, hypoxia may induce a modification of p53 that allows it to interact with transcriptional corepressor molecules. A more detailed analysis of proteins previously found to interact with p53, as well as hypoxia-induced protein binding partners, should be useful in understanding what modifications of p53 are needed to signal repression under hypoxic conditions (6, 15, 26). Previous studies using genetically matched cell lines with mutations affecting distinct apoptotic signaling molecules indicated that hypoxia-induced apoptosis is mediated through a mitochondrial signaling pathway requiring cytochrome c, Apaf-1, and caspase 9 (43). However, one crucial question is what signals the release of cytochrome c from the mitochondria. Many studies on DNA damage-induced apoptosis have indicated that a BH3-containing proapoptotic family protein, such as Bax from the bcl-2 family, promotes apoptosis through the mitochondria. Although Bax has been implicated in hypoxia/reoxygenation-induced apoptosis (5, 38, 45, 46), cells deficient in Bax undergo quantitatively and qualitatively similar amounts of apoptosis under hypoxic conditions (2). Recent studies have implicated other BH3 family members, such as PUMA, in hypoxia-induced apoptosis (25). However, these studies implicate PUMA in hypoxia-mediated apoptosis that occurred days after exposure to hypoxia and not in the short time frame observed in our system. In addition, we found that PUMA is expressed below the limits of detection in both our microarray and Northern analysis studies. Three additional members of the bcl-2 proapoptotic family of proteins, BNIP-3 and BNIP-3L (10) and NOXA (22), have been reported to be involved in hypoxia-signaled apoptosis. However, BNIP-3's BH3 domain is dispensable for hypoxia-mediated cell death, and it is unclear whether BNIP-3 induces apoptosis or necrosis (34, 36, 47). It is noteworthy that studies on the role of NIP3 in apoptosis have been performed using ectopic overexpression and may not be reflective of how NIP3 functions under the physiological stress of hypoxia. Likewise, a recent report has suggested that NOXA is both hypoxia inducible and a mediator of cell death when cells are deprived of both oxygen and glucose (22). The identification of an HRE in the promoter of NOXA suggests that it is a HIF-regulated gene and hence should modulate cell death in response to changes in oxygenation alone. We also found NOXA to be hypoxia inducible in human cells but could not find any difference in its expression in p53 wild-type or knockout cells. Therefore, it is probably unlikely that NOXA induction by hypoxia alone plays any role in p53-dependent apoptosis.
The recent findings of Johnson et al. indicate that a mouse expressing p5325,26 is embryonic lethal, raising the possibility that p5325,26 increases the sensitivity of hypoxic cells during embryonic development to apoptosis (19). We have now generated a comprehensive list of p53 effector genes in cells that undergo rapid p53-dependent apoptosis under hypoxic conditions. This list represents a strong starting point for us to identify the repressed targets critical for hypoxia-induced apoptosis. Comparison of the changes in gene expression between mice and tumors that express p53wt, p5325,26, or p5325,26,53,54 will provide new insight into how transactivation-deficient p53 signals an apoptotic genomic response under hypoxia and other nongenotoxic stresses.
| ACKNOWLEDGMENTS |
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This work was supported by an NIH grant (CA 88480) awarded to A.J.G.
| FOOTNOTES |
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Supplemental material for this article may be found at http://mcb.asm.org. ![]()
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