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Advances in Brief |
Division of Human Cancer Genetics, Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210 [Y-W. L., S. H. W., J. C. L., P. S. Y., T. H-M. H.], and Department of Pathology and Anatomical Sciences, Ellis Fischel Cancer Center, University of Missouri School of Medicine, Columbia, Missouri 65203 [F. R., H. S.]
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ABSTRACT |
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Introduction |
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TopABSTRACTIntroductionMaterials and MethodsResults and DiscussionREFERENCES |
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The dichotomy regarding the specific roles of these DNMTs in de novo and maintenance functions has recently been reexamined. Accumulating evidence has revealed a closer interplay among these DNMTs in the cell (5, 6, 7, 8) . For example, Rhee et al. (6) demonstrated that somatic cell knockouts of both DNMT3b and DNMT1 genes led to demethylation and reexpression of tumor suppressor genes in a colon cancer cell line. However, a single knockout of either DNMT3b or DNMT1 had minimal effects on DNA demethylation in this cell line (6 , 9) . This observation implies that DNMT3b and DNMT1 together, rather than DNMT1 acting alone, cooperate to maintain the DNA methylation pattern in this cell line (6 , 9) . In a separate knockout study, Liang et al. (5) demonstrated that whereas DNMT1 alone was able to maintain methylation of most CpG-poor sequences, both DNMT1 and one of the de novo DNMTs were required for methylation of a select class of repeat sequences, LINE-1, in mouse embryonic stem cells.
In this study, we examined the potential use of RNA interference in probing the functional relationship between DNMT3b and DNMT1 in the genome. RNA interference is a newly discovered phenomenon shown to silence genes via targeted mRNA degradation in mammalian cells (10) . Two siRNAs engineered specifically to knockdown, or suppress, these genes had differential effects on DNA methylation and gene reactivation in the ovarian cancer cell line CP70. We further demonstrated a synergistic relationship between DNMT3b and DNMT1 in this cell line and showed that siRNA is a powerful tool for interrogating the mechanisms of DNA methylation in the genome.
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Materials and Methods |
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TopABSTRACTIntroductionMaterials and MethodsResults and DiscussionREFERENCES |
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siRNA Transfections.
siRNAs for DNMT1 and DNMT3b were generated using the Silencer siRNA Construction Kit (Ambion) according to the manufacturer’s recommendations. Oligonucleotides used for the siRNA experiment were as follows:
DNMT1: sense strand, 5'-TCT GTC CGT TCA CAT GTG TTT CCT GTC TC; antisense strand, 5'-ACA CAT GTG AAC GGA CAG ATT CCT GTC TC (nucleotide positions 61,544–61,565; GenBank accession no. NM_001379);
DNMT3b: sense strand, 5'-AGA TGA CGG ATG CCT AGA GTT CCT GTC TC; antisense strand, 5'-CTC TAG GCA TCC GTC ATC TTT CCT GTC TC (nucleotide positions 46,915–46,936; GenBank accession no. NM_006892).
The underlined nucleotide sequences were used to anneal to the T7 promoter sequence. Using Klenow DNA polymerase, a fill-in reaction subsequently generated a double-stranded template from which complementary RNA products were reversibly transcribed by T7 RNA polymerase. Sense and antisense RNAs were hybridized to form the following siRNAs. The double-stranded sequence of DNMT3b-210 was as follows:
5'-AGAUGACGGAUGCCUAGAGUU-3';
3'-UUUCUACUGCCUACGGAUCUC-5'.
The double-stranded sequence of DNMT1-300 was as follows:
5'-UCUGUCCGUUCACAUGUGUUU-3';
3'-UUAGACAGGCAAGUGUACACA-5'.
One microgram of siRNA was resuspended in reduced serum RPMI-1670 (Invitrogen) and mixed with DMRIE-C Reagent (Invitrogen). The lipid-siRNA complex solution was then used to transfect 
106 CP70 cells for a 4–5-h period. The control cells were similarly transfected without siRNAs (i.e., vehicle only). After the transfection, cells were replenished with regular medium and left untreated for various time periods, and total RNA and DNA were then harvested for further analysis.
Cell Survival Assay.
CP70 cells were cultured in 6-well plates (2 x 105 cells/well). The cells were treated with 40 nM siRNA or mock-treated for 4–5 h and then were harvested at 4, 14, 28, and 56 h after the transfection. Cells were exposed to trypan blue (Sigma), and nonviable cells took up the dye. Both viable (unstained) and nonviable (stained) cells were counted, and the relative survival rate (%) of each siRNA treatment was then calculated as: siRNA-treated [unstained/(unstained + stained)] ÷ control [unstained/(unstained + stained)].
Real-Time PCR.
Total RNA (1 µg) was pretreated with DNase I to remove potential DNA contaminants and reverse-transcribed in the presence of SuperScript II reverse transcriptase (Life Technologies, Inc.). The cDNA generated was used for PCR amplification with appropriate reagents in the SYBR Green I PCR Kit (BioWhittaker) as recommended by the manufacturer. The reaction was carried out in 40–45 cycles in a Smart Cycler Real-Time PCR instrument (Cepheid). The primers used for PCR were as follows:
DNMT3b: sense primer, 5'-TAC ACA GAC GTG TCC AAC ATG GGC-3'; antisense primer, 5'-GGA TGC CTT CAG GAA TCA CAC CTC-3';
DNMT1: sense primer, 5'-GAG GAA GCT GCT AAG GAC TAG TTC-3'; antisense primer, 5'-ACT CCA CAA TTT GAT CAC TAA ATC-3';
TWIST (GenBank accession no. NM_000474): sense primer, 5'-GGA AGA GGT TCC CTA TTA GGC-3'; antisense primer, 5'-TCG GTC ATG AAG GAG ATA TAG ACG-3';
RASSF1A (GenBank accession no. NM_007182): sense primer, 5'-TTG GAG ACC CTG CAA ACA GAA CAG-3'; antisense primer, 5'-GAA GCA TTA AGG CAC ATG CTG TAC-3'; and
HIN-1 (GenBank accession no. AY040564): sense primer, 5'-ATC CCC GTG AAC CAC CTC ATA GAG-3'; antisense primer, 5'-CGT CTT GTC CTC AGG TGT AGA TGC-3'.
The PCR reaction was subject to a melting curve analysis to verify the presence of a single amplicon using the Smart Cycler software program (version 1.2d). In a few experiments, PCR products of the expected size were also visualized on agarose gels with ß-actin cDNA used as a loading control. All cDNA samples were synthesized in parallel, and PCR reactions were run in triplicate. Separate parallel reactions were run for GAPDH cDNA, using a series of diluted cDNA samples as templates to generate standardization curves. The mRNA levels were derived from the standardization curves and expressed as relative changes after normalization to those of GAPDH.
Western Blot Analysis.
siRNA-treated and control CP70 cells (1–2 x 106) were collected and lysed in a buffer containing proteinase inhibitors. Protein concentrations of the supernatant were determined with the Bio-Rad Assay Kit, and 6 or 60 µg of protein were subjected to SDS-PAGE and transferred to Immuno-Blot polyvinylidene difluoride membranes (Bio-Rad). Membranes were incubated in Tris-buffered saline with 5% nonfat dry milk containing mouse antibodies against DNMT1 or DNMT3b (Imgenex). Goat antimouse secondary antibodies labeled with horseradish peroxidase were used to bind the primary antibodies, and detection was performed by a chemiluminescence system as directed by the manufacturer (Bio-Rad).
COBRA.
Sodium bisulfite modification of genomic DNA was conducted using the CpGenome DNA Kit according to the manufacturer’s instructions (Intergen). Bisulfite-treated DNA (1 ng) was used as a template for PCR with specific primers flanking the BstUI sites located within the CpG island regions of interest (see examples in the upper panels of Fig. 3A
). Primers used for amplification were as follows:
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RASSF1A: sense strand, 5'-AAG TYG GGG TTY GTT TTG TGG TTT-3' (Y = mixture of G and T); antisense strand, 5'-CCC CAA ATA AAA TCR CCA CAA AAA T-3' (R = mixture of A and G);
HIN-1: sense strand, 5'-GGG AGT GAG GTT TGA TYG TTT TTG G-3'; antisense strand, 5'CTA AAA CCC TCT AAA AAC AAA CAA ACC C-3';
SC87F10 (E1F1A): sense strand, 5'-TTT ATT TTT ATT TTT GGG TAT GG-3'; antisense strand, 5'-CCA TAA AAC CAC CCA CCA CA-3';
CPG5B6 (CYP27B1): sense strand, 5'-AGG GGT TGA GAT ATG ATG TTT AGG-3'; antisense strand, 5'-ACC ATT TTC CCC AAC ACT CTA TC-3';
SC21G11 (HSPA.2): sense strand, 5'-TGT TGA TGA TGG GGT TGT AAA TT-3'; antisense strand, 5'-ACA AAA TCA CCA TCA CCA ATA AC-3'.
After amplification, 32P-incorporated PCR products were digested with BstUI (New England Biolabs), which recognizes sequences unique to the methylated alleles. The undigested control and digested DNA samples were separated in parallel on 8% polyacrylamide gels and subjected to autoradiography using a PhosphorImager (Amersham-Pharmacia).
Methylation Microarray Analysis.
Methylation amplicons were prepared essentially as described previously (11)
. Briefly, genomic DNA (1–2 µg) from siRNA-transfected and control cells was digested with MseI, a 4-base TTAA cutter that restricts bulk DNA into <200-bp fragments but retains GC-rich fragments. The 3'-overhangs of the digest were used to ligate PCR linkers H-24/H-12 (5'-AGG CAA CTG TGC TAT CCG AGG GAT-3' and 5'-TAA TCC CTC GGA-3'). The samples were further digested with the methylation-sensitive endonucleases HpaII and BstUI. PCR was then performed to preferentially amplify the methylated GC-rich fragments or fragments containing no internal HpaII or BstUI sites with use of the flanking linker H24 as a primer (11)
. After PCR, the control amplicon was labeled with Cy5 (red) fluorescence dye, whereas the siRNA-treated amplicon was labeled with Cy3 (green). The labeled samples were cohybridized to a panel of 8640 short CpG island tags (12)
arrayed on microscope slides. Posthybridization washing protocols were according to DeRisi et al.4
Signal intensities of hybridized spots were analyzed with the GenePix 4.0 software program (Axon). Because Cy5 and Cy3 labeling efficiencies varied among samples, we determined a global normalization factor for each microarray image as described earlier (11)
. An average value of 0 for a normalized log2[Cy5/Cy3] ratio indicates equal or similar methylation between siRNA-treated and control samples, whereas an average value >0 suggests demethylation. Ten MseI control fragments containing no methylation-sensitive test sites were included in the microarray panel, the normalized log2[Cy5/Cy3] ratios of which were expected to be 0. Goodness-of-Fit analysis was performed using the GraphPad Prim (version 4) program.
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Results and Discussion |
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TopABSTRACTIntroductionMaterials and MethodsResults and DiscussionREFERENCES |
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, shows a real-time RT-PCR analysis for one experiment in which 40 nM of DNMT3b-210 or DNMT1-300 or a combination of DNMT3b-210 and DNMT1-300 (40 nM each) were used to transfect CP70 cells. A mock transfection without siRNA was used as a control. We observed a >70% decrease in the level of DNMT3b mRNA 24 h after transfecting CP70 cells with DNMT3b-210 or the combined siRNAs. A similar effect on the level of DNMT1 mRNA was also observed in the DNMT1-300 treatment, but the level of this knockdown was less prominent (50% reduction) with the combined siRNAs. Consistent with these results, Western blot analysis showed that protein levels of DNMT3b and DNMT1 were affected by the siRNA treatments (Fig. 1C)
. This induced depletion is presumably achieved by targeted mRNA degradation (10
, 14)
. It has been suggested that once inside the cell, siRNAs assemble with certain proteins to form a multicomponent nuclease complex that recognizes specific DNMT mRNA populations by matching one of the two siRNA strands to the targets and directs the molecular cleavage (10
, 14)
. We also independently tested these siRNAs on several breast cancer cell lines and observed similar inhibitory effects (data not shown).
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. This growth suppression was noticeable 4 h after the transfection, and the effect was more prominent in DNMT1 single-knockdown and (DNMT3b + DNMT1) double-knockdown cells than in DNMT3b single-knockdown cells. The suppression was not a result of the transfection reagents because the overall survival of the control cells remained unchanged, but was likely attributable to the direct effect of RNA interference on the depletion of DNMT3b or DNMT1 in CP70 cells. It has been shown that depletion of DNMTs by antisense oligonucleotide inhibitors may induce apoptosis, leading to growth arrest of tumor cells (15
, 16)
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, methylated BstUI sites were detected in these CpG islands in the control cells, displaying restriction fragments with lower molecular weights in gel electrophoresis (Fig. 3A
, Lane 2). Demethylation of these sites was not seen in cells treated with DNMT3b-210 siRNA at day 1 (Fig. 3A
, Lane 3), but became detectable (10–20% demethylation) at day 2, showing the presence of some higher-molecular-weight fragments (Fig. 3A
, Lane 4). This effect (15–20% demethylation) was observed earlier, at day 1, in cells treated with DNMT1-300 siRNA, presenting a laddering pattern of DNA fragments (Fig. 3A
, Lane 5). However, demethylation was quite prominent in the combined treatment, showing at least 40% of BstUI demethylation at days 1 and 2 (Fig. 3A
, Lanes 7 and 8). The demethylation effect was diminished at day 6 (Fig. 3A
, Lane 9) and could be attributable to either the short half-life of siRNAs or the remaining untransfected cells overtaking the cultured dishes over time.
We further examined the effect of RNA interference on reactivating these methylation-silenced genes in CP70 cells. Real-time RT-PCR analysis of the abovementioned genes TWIST, RASSF1A, and HIN-1, was conducted on day 1 after the single or double siRNA treatment (Fig. 3B)
. Expression of these genes was undetectable in the control (vehicle only) cells. Reactivation (1–3-fold) of these genes was noticeable in the single DNMT3b- or DNMT1-knockdown cells. Nonetheless, this effect was markedly enhanced in the double-knockdown cells, leading to a 7-fold increase in the levels of TWIST and HIN-1 mRNAs and a 15-fold increase in RASSF1A relative to that of the control. It is interesting to note that this enhanced effect on DNA demethylation was not as dramatic as gene reactivation in the double-knockdown cells. As discussed earlier, the degree of DNA demethylation in the double-knockdown cells was only 2-fold greater than in the DNMT1 single-knockdown cells. One explanation is that DNMTs have been shown to bind chromatin-remodeling enzymes, such as histone deacetylases, and to participate in transcriptional repression independent of their methylating activities (20, 21, 22)
. Depletion of DNMTs via RNA interference therefore not only contributes to DNA demethylation, but also may dissolve the protein complexes for repressive chromatin, allowing for effective restoration of gene transcription.
To explore the effect of RNA interference on other CpG island loci, we used a microarray-based approach (11)
for a genome-wide survey of DNA methylation in CP70 cells. Cy3- and Cy5-labeled targets, which represented genomic pools of methylated DNAs, were prepared from siRNA-transfected and control cells, respectively, and cohybridized to microarray slides containing 8640 short CpG island tags (average, 700 bp; Ref. 11
). CpG island loci that were methylated in the control cells were expected to show positive Cy5 signals, which were defined by hybridization intensities two times greater than that of the background. These DNA fragments were protected from the digestion of methylation-sensitive endonucleases and thus could be amplified by PCR with flanking linkers. Unmethylated DNAs, however, were restricted by the endonucleases, could not be amplified by PCR, and thus were devoid of hybridization signals.
After the normalization of data, a total of 241 single-copy spots were scored as positive loci for DNA methylation in the control cells. We then determined the effect of demethylation on these loci in different siRNA treatments relative to the control. In Fig. 4A
, log2Cy5 (control)/Cy3 (siRNA-treated) ratios for these 241 loci are presented as scatter plots. Loci with greater demethylation are expected to have larger positive ratios because greater hybridization signals in the Cy5-labeled control targets are obtained relative to those of the Cy3-labeled test targets. On the other hand, loci exhibiting no change in methylation would show a ratio close to 0. Linear regression analysis was then performed based on curve fitting to the DNMT3b-knockdown cells. A significant difference was observed in the double-knockdown cells, showing a wider range of positive Cy5/Cy3 values than those of the DNMT3b single-knockdown cells (P = 0.0027). Although not statistically significant, the DNMT1 siRNA treatment seemed to show demethylation to a greater extent than that of DNMT3b siRNA. Because hybridization variability could occur among different microarray experiments, we repeated the study series. The comparable Ps for goodness-of-fit in this second study were 1.0000, 0.3677, and 0.0076. In addition, we conducted COBRA on three selected loci, the demethylation findings of which reflected the microarray results (Fig. 4B)
. A similar enhanced effect of demethylation was also seen in selected repetitive Cot-1 sequences, including Alu, rDNA, and 
-satellites, in the double-knockdown cells. (Fig. 4C)
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The present findings do not support a previous study that in somatic knockout cells lacking DNMT1, CpG island methylation can still be maintained (9) . Our view is further supported by a study using antisense oligonucleotides to deplete DNMT1 synthesis, which can induce demethylation and reactivation of the silenced CDKN2A gene in colon cancer cells (13) . One suggested reason for the discrepancy could be the difference in methodologies used to deplete cellular DNMT levels. The siRNA and antisense treatments transiently deplete DNMTs in an entire population of treated cells. In the somatic knockout study using homologous recombination, multiple rounds of clonal selection for cells with both alleles disrupted and with growth advantages were required. It is likely that during this selection process, the functional specificity of DNMT1 for maintenance methylation was somehow altered and became more dependent on the presence of DNMT3b. Nevertheless, our present results and the results from these previous studies (5, 6, 7) all point to a functional cooperation between DNMT3b and DNMT1 in cancer cells beyond the distinctive roles (i.e., de novo versus maintenance functions) depicted previously during embryonic development. To further unravel these roles in future studies, RNA interference can be an ideal tool for a systematic knockdown of genes governing methylation functions in normal and pathological conditions.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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1 This work was supported in part by National Cancer Institute Grants R33 CA-84701 and RO1 CA-69065. 
2 To whom requests for reprints should be addressed, at Room 514B, Division of Human Cancer Genetics, Medical Research Facility, The Ohio State University, 420 W. 12th Avenue, Columbus, OH 43210. Phone: (614) 688-8277; Fax: (614) 292-5995; E-mail: huang-10{at}medctr.osu.edu
3 The abbreviations used are: DNMT, DNA methyltransferase; siRNA, small interfering RNA; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; COBRA, combined bisulfite restriction analysis; RT-PCR, reverse transcription-PCR.
Received 2/ 6/03. Revised 8/ 7/03. Accepted 8/12/03.
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REFERENCES |
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0 suggests demethylation. B, confirmation of three selected loci by COBRA. Genomic DNA from siRNA-treated and mock-transfected cells was isolated for bisulfite treatment and subjected to PCR using flanking primers in a CpG island region. 32P-labeled PCR products were digested with BstUI and separated on an 8% polyacrylamide gel. Left panels, gel images of COBRA. The left-most lane of each panel is the BstUI-undigested (Undig) control. Dm, demethylated fragments; Me, methylated fragments. Right panels: quantitative results of COBRA. The percentage of demethylation was calculated as the intensity of demethylated fragments relative to the combined intensities of both demethylated and methylated fragments. C, demethylation of repetitive Cot-1 sequences by different DNMT siRNA treatments as evaluated by methylation microarray. The microarray images represent five individual spots selected from a pool of methylated Cot-1 sequences in untreated cells.