Decitabine treatment demethylates vast majority of high-confidence differentially methylated regions in HCT-116 colorectal cancer cells

Transcriptional enhancer binding analysis

DMRs were selected from Simmer et al.¹⁰. Genomic regions from table S4 of that publication were aligned to human genome 19 (hg19) using liftOver²⁶. UCSC genome browser was configured to visualize transcription factors and methylation status according to the following configuration: http://genome.ucsc.edu/s/williamhconrad/hg19%2Dall%2Dcell%2Dmethylation. Transcription factors were selected randomly from the track UCSC genome browser track "Transcription Factor ChIP-seq (161 factors) from ENCODE with Factorbook Motifs". 10 cell lines with transcription factor binding were recorded and 10 cell lines lacking transcription factor binding were recorded at each DMR. Cell lines were selected using a random number generator. Each transcription factor was recorded as a transcriptional repressor or enhancer according to UniProt²⁷. The methylation status was then recorded for each of those cell lines. Methylation was recorded as fully methylated, mostly methylated, majority methylated, half-methylated, minority methylated, mostly unmethylated, fully unmethylated, not detected, or not tested. The cell lines were then sorted into methylated or unmethylated. The number of repressors and enhancers was recorded, and a chi squared analysis was performed to compare differences in repressor and enhancer binding to methylated or unmethylated regions using excel Data are published as underlying data²⁸.

HCT-116 cell culture

HCT-116 cells were obtained from American type culture collection (ATCC; CCL-247) and cultured in McCoy’s 5A media (ATCC; 30-2007) in 10% fetal bovine serum (ATCC; 30-2007) and penicillin streptomycin (Thermo; 15140122). Cells were maintained in tissue culture flasks at 37 °C and 5% CO₂ according to established protocols from ATCC²⁹.

Clonogenic survival assay

To test the effect of decitabine on the clonogenic survival of HCT-116 cells, we used protocols adapted from Franken et al.³⁰ and Palii et al.³¹. Cells were plated at a density of 200 per well in a 6-well tissue culture plate. After overnight incubation, cells were treated with vehicle (anhydrous DMSO; Sigma; 276855), 0.1, 0.25, or 1 µM decitabine (Sigma; A3656). Cells were treated again after 24 hrs and then replaced with 2 ml of complete McCoy’s 5A media. After 12 days of growth, cells were fixed and stained with 10% w/v glutaraldehyde (Sigma; 340855), 0.5% w/v crystal violet (Sigma; C6158) in PBS (Sigma; 1408). After extensive rinsing in tap water, colonies were counted by eye. The average number of colonies was compared across the four conditions using a one-way ANOVA followed by Tukey’s HSD post hoc test.

Decitabine treatment and genomic DNA isolation

HCT-116 cells were cultured as described above. Exponentially growing cells were passaged to a density 20% confluency. The day following passage, cells were treated with 1 µM decitabine or DMSO. After 24 hours, treatment was repeated. After four additional days of incubation, cells were collected by trypsinization. 400,000 cells for each condition were collected and genomic DNA was isolated using the PureLink genomic DNA mini kit according to the manufacturers instructions (Thermo Fisher; K182001).

Global demethylation analysis

400 ng of genomic DNA isolated as above was treated with 10 units of HpaII (NEB; R0171S) at 37 C for 1 hr. genomic DNA digestion was then evaluated by 1% agarose (VWR; 97062-244) gel electrophoresis. DNA was stained with 1x sybr safe (VWR; 470193-138) and imaged on a Bio-rad chemidoc imaging system.

Bisulfite PCR

400 ng of genomic DNA isolated as above was bisulfite converted using the EZ DNA methylation kit according to the manufacturer’s instructions (zymo research; D5001). Bisulfite converted DNA was eluted in 10 µl at a concentration of approximately 40 ng / µl. Oligonucleotides for bisulfite PCR were designed using MethPrimer³². The positive strand sequence for a DMR was collected from UCSC genome browser and primers were designed for an amplicon between 150 and 400 nucleotides. Optimal annealing temperature for each primer pair were determined by testing a range of annealing temperatures between 44 and 66 °C for each primer pair against fully unmethylated and fully methylated genomic DNA (zymo; D5014). Primer pairs (Table 1), optimal annealing temperatures (Table 1), and PCR reaction conditions (Table 2), reaction master mix (Table 3) are provided in the indicated tables. Amplified DNA was purified from oligonucleotide primers and dNTPs using zymo DNA clean and concentrator-5 according to the manufacturer’s instructions (zymo; D4013). Samples were eluted in 10 µl of elution buffer and submitted for sequencing at the University of Chicago Comprehensive Cancer Center DNA sequencing and genotyping facility (Chicago, IL). Percent methylation was calculated using the relative peak height of cytosine and uracil at a given CpG site, as described previously. Peak height was quantified using Thermo Fisher Variant analysis app on the thermo fisher connect web site. Briefly, this cloud-based application processes .abi sequencing chromatogram files and returns base calls and peak height values for each peak on the chromatogram. The open source software Chromaseq can also extract identical base call and peak height values from .abi files³³. Briefly, chromaseq can be installed according to their web site. The .abi sequencing files can be viewed using this software. Selecting a base call will reveal the identical peak height value presented in the chromatogram as exported in the Thermo Fisher Variant analysis app.

Statistical analysis

All statistical analyses were performed using GraphPad Prism version 7.0d. To evaluate the effect of various doses of decitabine on clonogenic survival against a no-decitabine control, a one-way ANOVA with Tukey’s post hoc was performed to control for multiple comparisons (i.e. all drug conditions against the same control). To evaluate the percent methylation of DMRs in the presence or absence of decitabine, a one-way ANOVA was performed with Bonferroni’s post hoc test to allow for multiple comparisons (i.e. between control and decitabine treated for each DMR). The specific statistical tests used are also described in the figure legends.

Methylation inversely correlates with transcriptional enhancer binding

In mammals, cytosine methylation inversely correlates with gene expression^34,35. We sought to determine if our selected DMRs might regulate gene expression. Using the UCSC genome browser³⁶, we identified transcription factor binding data in our selected DMR regions from the encyclopedia of DNA elements (ENCODE) project³⁷. The ENCODE project has performed 2041 transcription factor CHIP-seq experiments across 90 cell lines^38,39. Transcription factor binding was observed at our DMRs (Figure 1). We hypothesized that if methylation silenced gene expression at the DMRs we selected, then we would see diminished binding of transcriptional enhancers in cell lines with methylation present at that DMR. For each of our six DMRs we observed TF binding across 20 cell lines selected by random number generator (see methods). We categorized the degree of TF binding and degree of methylation for these 10 cell lines (Underlying data for Table 4²⁸).

Figure 1. UCSC genome browser view of Transcription factors bound to the DKK3 DMR.

Representative screen capture of the UCSC genome browser view of the DKK3 DMR. Scale depicted in track 1 (black). DKK3 gene depicted in track 2 (blue). Transcription factor binding observed in ENCODE database depicted in track 3 (grey). CpG islands depicted in track 4 (green). CpG methylation as observed by reduced representation bisulfite sequencing in HCT-116 cells depicted in track 5 (red is 100% methylated, green is 0% methylated).

Indeed, we observed no transcriptional enhancers bound to methylated DMRs. Interestingly, binding of transcriptional repressors was also diminished at methylated DMRs, perhaps because methylation supplants the need for transcription factor repression. In general, transcriptional repressors and enhancers both bound more readily to cell lines with unmethylated DMRs (Table 4). The differences between repressor and enhancer binding in methylated and unmethylated DMRs was significantly different by chi-squared analysis (p<0.05). From these data, we conclude that methylation of the selected DMRs repress transcriptional enhancer binding across a broad range of cell lines.

Decitabine diminishes clonogenicity of HCT-116 cells and decreases global DNA methylation

The ability of a cancer cell to form a colony has been a long-standing measure for its survival in the host. Interventions that ablate clonogenicity increase patient survival⁴⁰. Decitabine is known to inhibit clonogenic survival of HCT-116 cells³¹, and we observe inhibition of clonogenic survival at similar doses ranging from 1 µM to 100 nM (Figure 2). Furthermore, decitabine treatment is known to increase sensitivity of HCT-116 genomic DNA to the restriction enzyme, HpaII, which is inhibited by CpG methylation⁷. Likewise, we observe that genomic DNA collected from HCT-116 cells treated for 48 hr with 1 µM decitabine was digested by decitabine (Figure 3). From these data, we conclude that decitabine inhibits the clonogenic survival of HCT-116 cells and also inhibits DNA methylation.

Figure 2. 1 µM Decitabine inhibits clonogenic survival.

Number of HCT-116 colonies detected by crystal violet staining 14 days after two 24-hour treatments of the indicated doses of decitabine. *p<0.05 ANOVA, Tukey's post-hoc.

Figure 3. Global DNA methylation is reduced by decitabine.

HCT-116 cells were treated with 1 µM decitabine or DMSO for 48 hrs. Genomic DNA was extracted and treated with the methylation-sensitive enzyme, HpaII as indicated. 400 ng of gDNA was separated by gel electrophoresis. Ladder indicated to the left of the gel.

Methylation at selected DMRs is decreased by decitabine

After observing global demethylation by 1 µM decitabine (Figure 3), we next sought to determine the degree of CpG methylation at DMRs in HCT-116 cells, and if those methylation sites were inhibited by decitabine. Using bisulfite PCR, we detected conversion of unmethylated cytosine to uracil (Figure 4a). Importantly, we both identified methylated CpG sites previously detected by reduced-representation bisulfite sequencing as part of the ENCODE project, and we also identified novel CpG sites in the region, adding resolution to the methylation status of these select DMRs (Figure 4b).

Figure 4. Methylation at selected DMRs is decreased by decitabine.

(a) Representative chromatograms of bisulfite PCR / sanger sequencing of the DKK3 DMR. Percent methylation quantified by peak height of C relative to C + T. (b) Mapping of bisulfite PCR results onto human genome 19. Scale depicted in track 1 (black). DKK3 gene depicted in track 2 (blue). CpG islands depicted in track 3 (green). CpG methylation as observed by reduced representation bisulfite sequencing in HCT-116 cells depicted in track 4 (red is 100% methylated, green is 0% methylated). Bisulfite PCR depicted in track 5 (DMSO) and track 6 (decitabine treated). The two grey bars show region sequenced. The red-green spectrum depict degree of methylation. (c) Quantification of percent methylation of sites depicted in (b). Percent methylation for each DMR as in (c). *p<0.05 ANOVA with Bonferroni’s post-hoc test. Columns and bars are mean and SEM, respectively.

We quantified the degree of CpG methylation at each site detected by bisulfite PCR in the presence or absence of decitabine. We observed statistically significant reductions in CpG methylation at all tested DMRs. From these data we can conclude that all colon cancer DMRs tested are hypermethylated in HCT-116 cells, that bisulfite PCR offers increased resolution at DMRs over HM450 array or RRBS, and that methylation at DMRs is reversable by 1 µM decitabine treatment.

Underlying data

Zenodo: williamhconrad/HCT116-DMR-bisulfite-PCR: bisulfite PCR repository under CC0 license. http://doi.org/10.5281/zenodo.3948439²⁸

This project contains the following underlying data:

Zenodo: williamhconrad/HCT116-decitabine-hub: Decitabine Hub repository under CC0 license. http://doi.org/10.5281/zenodo.3946753⁴¹.

This project contains the following underlying data that are used to build the UCSC genome browser public hub found at https://bit.ly/UCSC-DMR-methylation:

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).