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Previous Article | Next Article 
Molecular and Cellular Biology, July 2004, p. 5923-5936, Vol. 24, No. 13
0270-7306/04/$08.00+0 DOI: 10.1128/MCB.24.13.5923-5936.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.
Graduate Program of Pathobiology,1 Department of Medicine,2 Graduate Program in Cellular and Molecular Medicine,3 Program in Human Genetics and Molecular Biology, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205,7 Division of Pediatric Informatics,4 Division of Molecular Developmental Biology, Children's Hospital Research Foundation, Children's Hospital Medical Center,5 Department of Biomedical Engineering, University of Cincinnati, Cincinnati, Ohio 452296
Received 23 January 2004/ Returned for modification 15 March 2004/ Accepted 8 April 2004
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ABSTRACT |
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INTRODUCTION |
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A number of approaches that allow the prediction of transcriptional regulatory regions in any genomic region through comparisons of mouse and human sequences have been reported (4, 19, 21, 24). These approaches identify conserved regions that contain putative transcription factor binding sites. However, a purely computational approach tends to be replete with the uncertainty as to whether a predicted cis-regulatory module is biologically functional.
Several algorithms have been developed and experimentally evaluated for the discovery of candidate regulatory regions, such as those in the Drosophila genome (2, 26). In mammalian systems, we and other groups have evaluated the functionality of the transcriptional regulation of conserved cis elements. These studies, however, addressed individual genes or a small set of genes rather than a series of functionally related genes, such as those encoding a specific biochemical pathway. In our previous studies, putative direct Myc target genes were randomly selected and subjected to chromatin immunoprecipitation (ChIP) assays to identify Myc binding sites (43). In addition to class I genes in which Myc binding regions are highly conserved among species, we identified another group of genes termed class II genes, in which Myc binding regions do not contain conserved sequences (18). Thus, experimental validation of these computational approaches is particularly important in a well-defined model system involving a set of coordinately regulated genes, such as those encoding components of a metabolic pathway.
Although Myc and its target genes have been studied at a broader genome-wide level (6, 7, 14, 16, 17, 23, 25, 27, 29-31, 35, 41), the coupling of comparative interspecies sequence analysis and experimental validation of Myc target genes involved in a single metabolic pathway has not been thoroughly studied. It is particularly intriguing to note that ODC is not only the first identified bona fide Myc target gene, but it also contains a phylogenetically conserved intronic region bearing tandem canonical E boxes (1). MYC overexpression has been suggested to aberrantly enhance tumor glycolysis even in the presence of oxygen, a phenomenon termed the Warburg effect (8, 39). Thus, we chose Myc as a model transcription factor and the glycolytic genes as model target genes to predict Myc binding regulatory regions, which can then be experimentally tested. We have previously found that Myc specifically transactivates LDHA and increases the expression of other glycolytic enzyme genes (32, 37). Numerous studies using global gene expression profiling methods, such as serial analysis of gene expression (SAGE) and DNA microarrays, have found that Myc increases the expression of specific glycolytic enzyme genes, though these increases may be direct or indirect effects of Myc (27-29, 35).
To identify the direct target genes of Myc and its binding sites, we and other groups have applied various assays, including an in vitro reporter assay, electrophoresis mobility shift assay (EMSA), and the Myc-estrogen receptor (MYC-ER) system (11). Through the use of the MYC-ER system, several glycolytic genes, such as ENO1, GPI, HK2, LDHA, and PFKM, have been identified as direct targets of Myc (7, 29, 32, 35). However, these experimental approaches did not provide physical evidence that Myc directly activates the transcription of these genes through its association with specific genomic regions. The MYC-ER fusion protein system has been particularly used as a standard for the study of direct Myc target genes, as it allows the identification of MYC-ER-induced targets upon estrogenic ligand stimulation in the presence of cycloheximide, which prevents secondary transcriptional events (11). However, estrogenic ligands and cycloheximide used in these experiments may confound the effects of Myc, and the MYC-ER system is unable to reveal Myc target genes that are in feed-forward loops. In these loops, the expression of terminal target genes are dependent on both Myc and an intermediate transcription factor that is also a direct target of Myc.
We reasoned that functionally important genomic regions for Myc binding have been preferentially conserved in the direct target genes. Given that exonic sequence identity in the human and mouse genomes is estimated at about 85% (40), we have performed manual sequence alignments using dot plotting to identify nonexonic regions with at least 65% sequence identity in 30-bp segments. These cutoff criteria are adequately stringent to predict a particular class of Myc target genes, as previously reported (18, 43). We also used the Trafac server to identify potential Myc binding sites in glycolytic genes (19). A number of programs, including RepeatMasker (masking out repeat elements), PipMaker-BLASTZ (sequence alignment algorithm), and MatInspector Professional (transcription factor binding sequence scan), are integrated into the Trafac system to perform phylogenetic footprinting analysis (19). Trafac analysis predicts both canonical and noncanonical E boxes that reside in regions that have at least 50% sequence identity in the human and mouse genomes. Within these conserved segments, we sought to identify canonical Myc binding sites or E boxes with the consensus sequence 5'-CACGTG-3' and determine whether Myc could bind these regions by ChIP assays (10, 14, 23). By performing a ChIP assay, we can identify immunoprecipitated regions of the genome that are cross-linked to the bound Myc protein by amplifying the Myc-associated DNA fragments by PCR.
Our approach using Myc and 14 glycolytic genes as a model provides a unique opportunity not only to evaluate phylogenetic footprinting and determine the architecture of the Myc target glycolytic gene network but also to dissect the molecular basis of Myc-induced altered glucose metabolism. Our results provide evidence that MYC enhances aerobic glycolysis by directly up-regulating the expression of ENO1, GAPD, HK2, LDHA, PFKM, and TPI1 genes, whereas Myc binding to GPI, PGK1, and PKM is diminished or absent in the cases of BPGM, PGAM2 (muscle specific), and PKLR (liver specific). This study indicates that conserved, canonical E boxes are predictive of significant Myc binding to glycolytic target genes, but the absence of canonical E boxes does not exclude the possibility of significant Myc association.
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MATERIALS AND METHODS |
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Cell lines. The human Burkitt's lymphoma cell line P493-6 carrying an inducible MYC repression system (35) and human breast epithelial A1N4 cells (22) were used for ChIP analysis. P493-6 cells were maintained in RPMI 1640 medium with 10% fetal bovine serum (GIBCO/BRL) and 1% streptomycin and penicillin (Invitrogen). A1N4 cells were maintained in Improved MEM Zinc Option medium (Invitrogen) with 0.5% fetal bovine serum (GIBCO/BRL), 10 ng of epidermal growth factor (EGF) (Invitrogen) per ml, 0.5 ng of hydrocortisone (Clonetics) per ml, and 5 ng of insulin (Clonetics) per ml. Incubating P493-6 cells with 0.1 µg of tetracycline per ml for 72 h led to significant repression of MYC.
ChIP assay. P493-6 cells left untreated or treated with tetracycline for 72 h and human breast epithelial A1N4 cells stimulated by 20 ng of EGF (Invitrogen) per ml for 24 h were used for all ChIP assays. Cells were cross-linked by formaldehyde, and chromatin was immunoprecipitated as described previously (5). The rabbit polyclonal Myc antibody (sc-764; Santa Cruz Biotechnology) and human hepatocyte growth factor (HGF) antibody (sc-7949; Santa Cruz Biotechnology) were used to precipitate chromatin. The total input was the supernatant from the no-antibody control. For a control, some samples were treated the same as the other samples, but these samples had no chromatin (mock control samples). Real-time PCR quantitation of precipitated chromatin fragments was performed using a SYBR green core reagent kit (PE Applied Biosystems) on an ABI 7700 sequence detection system (PE Applied Biosystems) according to the manufacturer's instructions. Primers were designed using Primer Express software (PE Applied Biosystems) (see Table S1 in the supplemental material for the primer sequences for the ChIP assay). The data were analyzed by SDS 1.91 software (PE Applied Biosystems). Four serial 10-fold dilutions of total input DNA were used to generate a standard curve for each primer pair. Relative amounts of each chromatin fragment were then extrapolated on the basis of their threshold cycle values and determined by the percentage of the total input DNA. For each amplification, melting curves and gel electrophoresis of the PCR product were used to verify the identities of the PCR products. All real-time PCRs were performed in triplicate.
RNA analysis. MYC and glycolytic mRNA levels were determined by Northern blot analysis or quantitative real-time reverse transcription-PCR (RT-PCR). Total RNA was isolated from P493-6 cells using Trizol (Invitrogen). Five micrograms of RNA was used in Northern blot analysis. RNA was subjected to 1.2% agarose electrophoresis and transferred to a nylon membrane (Nytran). The membrane was probed with a human MYC gene probe or a glycolytic gene probe which had been labeled with 32P using a random primer labeling kit (Stratagene). An ethidium bromide-stained agarose gel of 18S rRNA was used as a loading control.
Quantitative real-time RT-PCR was performed using TaqMan one-step RT-PCR master mix kit (PE Applied Biosystems) with probes and primers. Alternatively, cDNA was reverse transcribed from the total RNA (2 µg) using TaqMan reverse transcription reagents (PE Applied Biosystems), and subsequent real-time PCR of cDNA was performed using the SYBR green core reagent kit on an ABI 7700 sequence detection system. Primers and probes were designed by the Primer Express software (see Table S2 in the supplemental material for the primers and probes). Amplified fragments span intron/exon boundaries in the cDNA sequences. The expression level of human 18S RNA was determined by a predeveloped mixture of TaqMan probe and primers (PE Applied Biosystems) and used for normalization. All PCRs were performed in triplicate.
Western blotting.
Equal amounts of protein extracted from P493-6 cells were subjected to electrophoresis on sodium dodecyl sulfate-10% polyacrylamide gels. Monoclonal anti-Myc antibody (9E10; Oncogene Research Products) and anti-
-tubulin antibody (CP06; Oncogene Research Products) were used for immunoblotting.
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RESULTS |
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Predicted conserved canonical E-box regions bind to Myc in vivo. To determine whether Myc binds conserved canonical E boxes, we performed ChIP assays. In addition to ENO1, HK2, and LDHA, which display significant conservation (Fig. 1), we selected additional human glycolytic genes to determine whether nonconserved canonical E boxes might be bound by Myc. Human GPI, PFKM, and PKLR genes contain canonical E boxes that are not found in the mouse orthologs. BPGM, PGAM, PGK1, and PKM2 do not have conserved E boxes (Fig. 2A). It should be noted, however, that intronic PGK1 conserved canonical E boxes were detected by Trafac analysis (Fig. 3). By lowering the stringency of our manual alignment to 50% identity, we were able to align these E boxes (data not shown). The P493-6 B-cell line was chosen for the ChIP assay (35, 36). These cells carry a tetracycline-responsive MYC expression system. Tetracycline significantly represses ectopic Myc protein expression, resulting only in residual endogenous Myc expression (Fig. 4A). MYC mRNA level was also significantly repressed, as previously reported (43). Removal of tetracycline resulted in a significant induction of MYC and enhancement of glycolysis (36).
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The binding of Myc to the promoter or intron 1 regions of ENO1, HK2, and LDHA also correlated with gene expression. Using P493-6 cells, we observed that the mRNA levels of these three genes were also significantly higher in untreated P493-6 cells (high MYC) than in tetracycline-treated P493-6 cells (low MYC) (Table 1). The increased expression of these genes in response to elevated Myc provides further evidence that these genes are functional direct Myc targets.
Identification of Myc binding regions not predicted by phylogenetic footprinting in GAPD and TPI1. Myc induces the expression of both GAPD and TPI1, although they do not contain canonical E boxes (Fig. 2B and Table 1). To determine whether Myc could directly bind to regions in the promoter or intron 1, we used scanning ChIP assay (42). First, we used five PCR primer pairs to scan the human GAPD locus at approximately 1-kb intervals (regions A, B, C, E, and G) (Fig. 7A). Using the P493-6 cell system, significant Myc binding was found in region G that spans approximately 40 bp upstream of the transcriptional start site through the entire exon 1 (Fig. 7B). We then considered the role of noncanonical E boxes, as we previously demonstrated Myc binding to conserved, noncanonical E boxes in vivo (43). We identify four noncanonical E boxes in the human GAPD gene and seven noncanonical E boxes in the mouse Gapd gene (Fig. 7A) (see Materials and Methods for the sequence variations of noncanonical E boxes). Two pairs of human noncanonical E boxes are located either within 0.4 kb or within 2 kb upstream of the transcriptional start site. However, these noncanonical E boxes were not significantly conserved. We then performed an extended scan with additional PCR primer pairs to pinpoint the fragments that lie within 100 bp of the noncanonical E boxes (regions D and F) (Fig. 7). Region H was used as an additional control. Figure 7B demonstrates Myc binding to region F (0.8% of total input) and region D (0.3% of total input). These results suggest that Myc binds a GAPD promoter region containing noncanonical E boxes that are not conserved in the mouse Gapd gene.
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DISCUSSION |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Phylogenetic footprinting analyses by both manual alignment and Trafac analysis predicted evolutionarily conserved, canonical Myc binding sites in ENO1, HK2, and LDHA, which were all confirmed by ChIP assay results. We observed that in vivo, Myc binding correlated with the induction of glycolytic target gene expression by Myc. These genes belong to what we previously termed class I Myc target genes, which contain conserved canonical E boxes (18). Since promoter-reporter assays and EMSA do not reflect in situ Myc binding, we had not included these assays in the present study. Nevertheless, we previously demonstrated for LDHA that Myc binds the highly conserved LDHA E boxes in EMSA as well as in promoter-reporter assays and that mutation of the E boxes rendered the promoter unresponsive to Myc (37). Given the limitations of EMSA (18) and considering the fact that even artificial promoters bearing E boxes are responsive to Myc in transient-transfection assays (20), we have focused on ChIP as a measure of in vivo Myc binding.
All other glycolytic genes studied do not have evolutionarily conserved canonical E boxes, although most of the glycolytic genes we studied were up-regulated in the presence of high levels of Myc. Because human GAPD and TPI1 genes are induced by MYC but do not contain predicted Myc binding sites or canonical E boxes, we sought to determine whether Myc binds these genes by scanning ChIP assays. The ChIP assay identified strong Myc binding to the regulatory regions of GAPD and TPI1, providing evidence that GAPD and TPI1 are direct Myc targets. However, the correlation between Myc binding and phylogenetic conservation in GAPD and TPI1 is less clear. TPI1, which is induced by Myc, has a conserved noncanonical E box (5'-CACATG-3') in the upstream region. However, Myc bound best to the intron 1 region that contains two noncanonical E boxes (5'-CACATG-3' and 5'-CGCGTG-3') that correspond to a mouse canonical E box. These intron 1 regions were aligned by Trafac analysis, but not by dot plotting. Instead, dot plotting identified different areas of noncanonical E-box conservation in the intron 1 regions (Fig. 8A and C). GAPD, which is also induced by Myc, has no conserved canonical or noncanonical E boxes. With GAPD, Myc bound best to the human promoter region F that is near two nonconserved, noncanonical E boxes (5'-CGCGTG-3' and 5'-CGCGAG-3'). Hence, both GAPD and TPI1 belong to what we previously termed class II direct Myc target genes, whose Myc binding sites either drifted during evolution or are newly acquired (18).
The human PFKM gene contains a canonical E box in the promoter region, which is bound well by Myc, although this canonical E-box region is not conserved in the rat Pfkm gene. Most of the corresponding mouse sequence is currently unavailable. Myc slightly bound the human PGK1 region with one upstream and two intron 1 canonical E boxes. Myc bound the human GPI promoter region with one canonical E box. It is less clear whether Myc bound the human PKM2 region near an intron 1 canonical E box, when a control region several kilobases upstream is considered (Fig. 5B). No Myc binding was detected in the canonical E-box regions of human BPGM, PKLR, and PGAM2 genes. We were unable to identify suitable primers for quantitative PCR in the ALDOA and HK1 loci. In aggregate, these observations indicate that Myc binds weakly to glycolytic genes that do not contain conserved Myc canonical binding sites. Because we examined Myc binding only in canonical E-box regions for the remaining genes (Fig. 2A), we cannot exclude the possibility that Myc may bind noncanonical E boxes or unknown novel binding sites.
Since tetracycline treatment suppresses only ectopic Myc expression in P493-6 cells and does not affect endogenous Myc expression, this study provides a unique opportunity to examine endogenous Myc and ectopic Myc binding to the same genes. Only class I (ENO1, HK2, and LDHA) and class II (GAPD and TPI1) genes demonstrate binding by endogenous Myc (Fig. 5A, 7B, and 8D). Intriguingly, while both HK2 and LDHA displayed a corresponding enhanced binding of ectopic Myc to the same regions, ectopic Myc binding to ENO1 is higher in promoter region B than in the intronic region C that is bound well by endogenous Myc (Fig. 5A and 6). Through studying the human A1N4 breast epithelial cells, in which endogenous Myc is induced by the growth factor EGF, we also observed that intronic region C of ENO1 is better bound by endogenous Myc than the promoter region B. High basal Myc binding to ENO1 region C was observed compared to either LDHA or HK2. With GAPD, there was significant binding of ectopic Myc to region D, which was not bound by endogenous Myc, although this level of binding might be at the threshold of detection. With PFKM, PGK1, GPI, and PKM2, moderate to diminished binding was detected only with ectopic Myc. With endogenous Myc, phylogenetic footprinting was highly predictive of Myc binding to the conserved regions bearing canonical E boxes.
So why are these specific regions conserved in ENO1, HK2, and LDHA? As less than 20% of nonexonic sequence is conserved in the human and mouse genomes, significantly high level of conservation, which is more than 65% sequence identity at and around Myc binding regions extending 30 to more than 100 bp, shown in ENO1, HK2, LDHA, and TPI1 genes may have an impact on Myc-mediated transcriptional regulation. One possibility is that these extended conserved sequences may contain binding sites for other transcription factors or chromatin remodeling proteins, which could affect the transcriptional activity of Myc (12). Our preliminary Trafac analysis suggests that conserved binding sites for the transcription factors ETS, AP4, Sp1, CREB, and HIF-1 are found overrepresented near conserved Myc E boxes in glycolytic genes (A. G. Jegga, unpublished data). In particular, among the 10 glycolytic genes with more than three other conserved transcription factor binding sites near a conserved E box, only ENO1, HK2, and LDHA lack clusters containing AP4 sites with an E box (Jegga, unpublished). It will be intriguing to determine whether the lack of AP4 sites in ENO1, HK2, and LDHA contributes to their robust response to Myc. At this time, we are evaluating these candidate transcription factors, but the findings are beyond the scope of this report.
While previous studies reveal that hypoxia induces glycolysis through the HIF-1 transcription factor, our studies demonstrate that in normoxia, Myc can induce most glycolytic genes including ALDOA, ENO1, GAPD, GPI, LDHA, HK2, PFKM, PGK1, PKM, and TPI1 (Fig. 9). This supports the hypothesis that the propensity for some tumors to undergo aerobic glycolysis (Warburg effect), in which glucose is converted to lactate despite the availability of oxygen, could be the result of Myc activation of glycolytic gene expression independent of hypoxia. Of the Myc-induced genes, HK2, PFKM, and PKM were previously considered to be important rate-limiting regulatory points in glycolysis. However, according to metabolic control analysis, there are no so-called rate-limiting enzymes in a pathway. Rather, the control of metabolic flux through a pathway is shared between all enzymes in different proportions such that coordinate regulation of a number of enzymes in a specific pathway is sufficient to affect overall metabolic flux. Hence, the induction of genes encoding key enzymes by Myc appears sufficient for enhanced glycolytic flux.
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ACKNOWLEDGMENTS |
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We thank L. Lee, A. Chakravarti, and J. Yustein for helpful comments, D. Eick for P493-6 cells, and P. Farnham for ChIP protocols.
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FOOTNOTES |
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Supplemental material for this article may be found at http://mcb.asm.org/.
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