3-D DNA methylation phenotypes correlate with cytotoxicity levels in prostate and liver cancer cell models
© Gertych et al; licensee BioMed Central Ltd. 2013
Received: 20 June 2012
Accepted: 14 January 2013
Published: 11 February 2013
The spatial organization of the genome is being evaluated as a novel indicator of toxicity in conjunction with drug-induced global DNA hypomethylation and concurrent chromatin reorganization. 3D quantitative DNA methylation imaging (3D-qDMI) was applied as a cell-by-cell high-throughput approach to investigate this matter by assessing genome topology through represented immunofluorescent nuclear distribution patterns of 5-methylcytosine (MeC) and global DNA (4,6-diamidino-2-phenylindole = DAPI) in labeled nuclei.
Differential progression of global DNA hypomethylation was studied by comparatively dosing zebularine (ZEB) and 5-azacytidine (AZA). Treated and untreated (control) human prostate and liver cancer cells were subjected to confocal scanning microscopy and dedicated 3D image analysis for the following features: differential nuclear MeC/DAPI load and codistribution patterns, cell similarity based on these patterns, and corresponding differences in the topology of low-intensity MeC (LIM) and low in intensity DAPI (LID) sites.
Both agents generated a high fraction of similar MeC phenotypes across applied concentrations. ZEB exerted similar effects at 10–100-fold higher drug concentrations than its AZA analogue: concentration-dependent progression of global cytosine demethylation, validated by measuring differential MeC levels in repeat sequences using MethyLight, and the concurrent increase in nuclear LIM densities correlated with cellular growth reduction and cytotoxicity.
3D-qDMI demonstrated the capability of quantitating dose-dependent drug-induced spatial progression of DNA demethylation in cell nuclei, independent from interphase cell-cycle stages and in conjunction with cytotoxicity. The results support the notion of DNA methylation topology being considered as a potential indicator of causal impacts on chromatin distribution with a conceivable application in epigenetic drug toxicology.
KeywordsDNA methylation phenotype Chromatin distribution High-throughput cell assay 3D image analysis MethyLight Repetitive element Epigenetic drug
DNA methylation is a crucial epigenetic modification of the human genome beyond the DNA sequence level that is involved in regulating many cellular processes. Cancer cells frequently exhibit abnormally high levels of DNA methylation in gene-specific CpG-rich promoter regions[2–5]. Furthermore, DNA methylation also occurs at non-CpG islands within the major part of the genome known as heterochromatin[6, 7], which plays a key role in nuclear architecture and genome stability[8–10]. It is now clear that DNA hypomethylation in human cancer is also very frequent and affects more cytosine residues than does DNA hypermethylation, accounting for a net loss of 5-methylcytosine (global DNA hypomethylation), as observed in many cancers[11–14]. The reversible nature of epigenetic imbalances in various types of cancers constitutes an attractive therapeutic target. The goal of epigenetic therapy in cancer is the reprogramming of aberrant cells towards normal phenotypes. In this regard, the drug discovery field has so far been mostly focusing on screening the effect of candidate agents on the levels of molecular cell signaling and metabolism. However, in recent years of the post-genomic era, chromatin conformation and the higher–order genome organization, which set the framework for the global orchestration as well the locus-specific regulation of gene expression in the human cell nucleus[15–18], are gaining more attention in therapy; the reason being that these functional structures can become affected as a consequence of epigenetic interference by chromatin-modifying agents such as inhibitors of DNA methylation.
Catalytic DNA methyltransferase (DNMT) inhibitors have been so far categorized into two classes: nucleoside analogues and non-nucleoside analogues. The two nucleoside analogues, 5-azacytidine (AZA, Vidaza™) and 5-aza-2′-deoxycytidine (decitabine, Dacogen™) are the most advanced in their category, having received US Federal Drug Agency (FDA) approval for their use in treating myelodysplastic syndrome (MDS) and hematopoietic malignancies[21, 22]. Zebularine (ZEB) or 1-β-D-ribofuranosyl-2(1H)-pyrimidone has recently emerged as a new DNMT inhibitor (DNMTi), with properties that makes it a potential drug candidate for oral administration: (i) stability at pH ranges between 1.0 and 7.0 in aqueous solutions, (ii) far less toxicity than AZA and decitabine to cultured cells, and (iii) no detectable toxicity in a T-cell lymphoma mouse model[23–27].
The specific mechanism of DNA methylation alterations induced by azacytidine nucleoside analogues is complex and not fully understood. Azacytidine is thought to form a stable covalent bond with DNMTs after its incorporation into genomic DNA, thereby trapping the enzyme and sequestering it from transferring methyl groups to other regions of the genome[28–30]. Such a passive mechanism of DNA demethylation as a result of exposure to DNMTi has been proposed and is thought to progress with several cell divisions, after which DNMT levels increase and specific gene regions show re-methylation. Azacytidine treatment of cells also was shown to induce degradation of DNMT1 via the ubiquitin-activating proteosomal pathway, as well as p53-mediated cell cycle arrest and DNA repair. Chromatin packaging and organization are altered in cells treated with azacytidine. Nucleosome depletion of symmetrically demethylated gene loci have been demonstrated after drug treatment. However, it should be noted that there are additional reports indicating that genomic regions with AZA DNA-DNMT adducts are improperly packaged and transcriptional activation can only occur with DNA repair and recruitment of other protein factors[34, 35].
Cell culture and drug treatment
DU145 human prostate cancer cells were obtained from American Tissue Culture Collection (catalog number HTB-81, ATCC). The vendor certifies authentication of cells using a variety of techniques such as short tandem repeat (STR) analysis and cytogenetic analyses (G-banding, fluorescence in situ hybridization). Huh-7 cells were a gift from Dr. Vaithilingaraja Arumugaswami (Cedars-Sinai Medical Center, Los Angeles, CA). The cells were propagated for less than six months after receipt and resuscitation. Cells were grown in Dulbecco’s modified Eagle’s medium (DMEM, Cellgro) supplemented with 10% newborn calf serum, and 1% antibiotic/antimycotic (1000 units/ml penicillin G sodium, 10 mg/ml streptomycin sulfate) (Gemini Bio-Products), in 5% CO2, 37°C. Cells were plated at 1 × 105 cells onto coverslips in multi-well plates in replicates, and allowed to attach for 24 hours. For dose dependency assay, wells were divided into two groups: (i) control populations that were not treated for 72 hours, and (ii) populations of cells treated with two different drugs at different concentrations for 72 hours: 0.5 μM, 1 μM, 2.5 μM, 5 μM, 10 μM and 20 μM of 5-azacytidine (Sigma-Aldrich), and 8 μM, 40 μM, 200 μM, 500 μM and 1000 μM of zebularine (Sigma-Aldrich), all in DMEM. For all cells, drug concentrations were freshly prepared prior to administration, and the drug-medium mixture was changed every 24 hours. Subsequently, cells were partially fixed for immunofluorescence and partially harvested for cytotoxicity testing by flow cytometry.
DU145 prostate cancer cells were arrested in G0/G1 and G2-phases following previously established protocols[60, 61]. Briefly, cells were seeded onto glass coverslips at a concentration of 105 cells/ml for immunofluorescence staining and subsequent imaging via confocal microscopy. A parallel set of cultures (at the same concentration) was maintained in culture flasks, for flow cytometry. All cells were first allowed to attach and grow for 24 hours in regular proliferative medium (DMEM/10% FBS/1% penicillin/1% streptomycin), which was then replaced by serum-deprived DMEM for 72 hours, followed by a recovery period of 4 hours, in which cells were maintained again in regular proliferative medium. G0/G1 populations were partially fixed at this point for use in either immunocytochemistry or FACS. The remainder cultures were processed for a double-thymidine block to enrich cells in G2-phase: (i) first blocking with deoxythymidine (Sigma) at 2 mM for 18 hours, (ii) recovery in regular proliferative medium for 12 hours to escape S-phase, (iii) second blocking with 2 mM deoxythymidine for another 18 hours, and (iv) second recovery in regular proliferative medium for 8 hours, to release cells into G2. At this point G2-cells were fixed for further experimentation. Enrichment efficiency was checked by propidium iodide (PI) staining of cells and nuclear DNA content analysis, following standard protocols as previously described in Wong et al.: cells were fixed in 70% ethanol/PBS and maintained for at least 4 hours at 4°C; then incubated in 5 μg/ml PI (Sigma) for 30 minutes at 37°C immediately prior to flow cytometry with a FACScan (Becton Dickinson). FACS data were analyzed using the ModFit LT program (Verity Software House, Topsham, ME, USA).
Induction of apoptosis and cell viability was analyzed in cells that were treated as replicates in parallel to cells that were subsequently analyzed by immunofluorescence. For that purpose, 2×105 cells/ml were stained with Annexin V (7-AAD) and PI, respectively. In essence, trypsinated cells from parallel wells were processed with the Annexin V-FITC Apoptosis Detection Kit I (BD Biosciences). Cells (1×105) were incubated for 15 minutes at room temperature with 7-AAD and PI in a total volume of 510 μl comprised of 5 μl of each of the fluorescent dyes, each and 500 μl of 1X binding buffer. Controls with unstained cells and cells stained with either dye alone were used for FACS setup. Samples were analyzed at emission wavelengths of 530 nm (for Annexin V-FITC) and 650 nm (for PI) using FACScan. The fluorescence of 104 cells was acquired and analyzed with CellQuest software (Becton Dickinson).
Immunofluorescence and image acquisition
In order to preserve the three-dimensional structure, cells cultured on glass coverslips in 12-well microplates (Costar, Corning) were fixed with 4% paraformaldehyde/phosphate buffered saline (PBS) (Sigma-Aldrich) and processed for immunofluorescence as previously described. The following antibody sets were used: a monoclonal mouse anti-5-MeC antibody (Clone 33D3, Aviva Systems Biology, San Diego, CA) together with an Alexa488-conjugated polyclonal donkey anti-mouse IgG (H + L) (Invitrogen), and a polyclonal rabbit anti-H3K9me3 antibody (Active Motif) together with an Alexa647-conjugated chicken anti-rabbit IgG (H + L) (Invitrogen). All specimens were counterstained with DAPI. Specimens were imaged by a confocal laser-scanning microscope (TCS SP5 X Supercontinuum, Leica Microsystems Inc.) that allows for any excitation line within the continuous range of 470 to 670 nm, in 1 nm increments. The system was additionally equipped with a 405 nm diode laser line for excitation of DAPI fluorescence. Serial optical sections were collected at increments of 200–300 nm with a Plan-Apo 63X 1.3 glycerol immersion lens (pinhole size was 1.0 Airy unit). To avoid bleed-through, the imaging of each channel was performed sequentially. The typical image size was 2048 × 2048, with a respective voxel size of 116 nm × 116 nm × 230.5 nm (x, y, and z axes), and resolution was 12 bits per pixel in all channels. Fluorescence intensity of MeC-signals and DAPI-signals from optical two-dimensional sections were recorded into separate 3D channels. Raw images were obtained as Leica Image Format (lif) and offline-converted to a series of TIFFs for downstream image analysis.
3D image analysis
Image analysis was performed in three main steps, as comprehensively described in[43, 44]: 1) image segmentation resulting in the delineation of a 3D shell for each individual nucleus; 2) extraction of MeC and DAPI signal intensity distributions within each 3D shell; 3) assessment of cell population heterogeneity through 2D histograms of MeC versus DAPI distribution patterns, utilizing K-L divergence, and 4) the mapping of LIMs and LIDs within individual nuclei. A newly added analytical component for this study was the calculation of mean intensity of MeC signals. Images in each two-channel 3D stack were acquired under nearly identical conditions and modality settings, and so the drift of the settings during acquisition is considered minimal and can be neglected. For codistribution analysis, the MeC and DAPI signals were mapped as respective 2D scatter plots, and following the Kullback–Leibler (KL) divergences were calculated between individual 2D plots (nuclei) and the reference 2D plot (cumulative plot from all nuclei in one drug/concentration experiment). Based on the KL value, cells were categorized as: similar KL G ∈ [0, 0.5), likely similar KL G ∈ [0.5, 2), unlikely similar KL G ∈ [2, 4.5), and dissimilar KL G ∈ [4.5, ∞) in order to evaluate a ratio of similar and dissimilar cells. For localization of resulting LIM and LID sites, the nuclei were analyzed by an algorithm introduced in. Briefly, segmented nuclei were eroded at a constant voxel rate of 1.32 μm × 1.3 μm × 0.25 μm, and MeC and DAPI signals were recorded as integrated intensity values within each nuclear shell. Then, local densities of LIM and LID sites as well as LIM and LID profiles were determined for each nuclear shell as the subset of voxels within a defined intensity range between two thresholds measured separately for each channel (MeC and DAPI): tbcg is the threshold value for the background, and tQ, which separates high-amplitude from low-amplitude intensities, as explicitly described in. All analytical findings related to image processing including numerical results, MeC/DAPI codistribution patterns, individual and combined MeC/DAPI images, LIM/LID outputs of cells were exported by means of a graphical user interface to text or graphics files respectively for further statistical analyzes. A built-in pseudo-coloring of KL divergence, and LIM and LID site shading was superimposed onto original images to facilitate visual reading and evaluation of experimental data.
Antibody specificity and sensitivity test
MethyLight assay for repetitive elements
MethyLight assays for measuring DNA methylation content of Alu, Satα and Sat2 repeat sequences were performed as previously described by Weisenberger et al.. Briefly, genomic DNA was extracted from harvested Huh-7 cells and 1 μg of genomic DNA was converted with bisulfite and recovered using the Zymo EZ DNA methylation kit (Zymo Research, Irvine, CA), as recommended by the manufacturer. Aliquots of the bisulfite-converted DNAs were used in separate MethyLight assays as previously described. MethyLight data specific for the three types of repetitive elements were expressed as percent of methylated reference (PMR).
Zebularine exerts a comparably lower degree of cytotoxicity than 5-azacytidine
We evaluated cultured DU145 prostate cancer cells and Huh-7 hepatocellular carcinoma cell lines for imaging-based DNA methylation analysis using the 3D-qDMI system to determine DNA methylation phenotypes of cells after 5-zacytidine and zebularine administration. These drugs have been used with a variety of cancer cell lines, including DU145 and Huh-7 cells, and described as being compatible to a large extent with cell viability and cell division[25, 40, 53–59]. The azanucleoside drug concentrations applied here were in the range as previously reported by investigations utilizing molecular nucleic acids-based assays.
High variation in DNA demethylation and differential drug sensitivity revealed by cell-by-cell imaging
The experimental results confirm the hypomethylating effect of both drugs; the increase of drug concentration causes a progressive loss of globally measured MeC-specific signal in nuclei (I MeC) and a decrease of I MeC spread (Figure4). Interestingly, AZA, at the highest concentration applied (20 μM), reduced the I MeC stronger in Huh-7 cells (88%) than in DU145 cells (75%), whereas ZEB at the highest concentration (1000 μM) reduced I MeC in DU145 cells at 72% versus 50% in Huh-7 cells, on average. However, when comparing global DNA methylation of cell nuclei at the equitoxic levels, ZEB showed a much stronger DNA hypomethylation effect than its nucleoside analogue at IC10 — 15% versus 5% for DU145 and 43% versus 18% for Huh-7 — then a milder effect at IC50: 54% versus 69% for DU145 and 50% versus 80% for Huh-7 cells. These results are in agreement with previous studies[24, 26, 54], and underline the less toxic effect of zebularine on cells and the milder nature of the drug when compared to AZA. In other words, AZA-treatment in both cell lines showed an approximate reduction of I MeC at 63% between IC10 and IC50 concentrations, whereas the I MeC reduction leap was significantly different between ZEB-treated cells: I MeC ≈ 39% for DU145 and only 7% for Huh-7 cells. The data indicate that if DNA hypomethylation effects would be influencing cytotoxicity, dose–response may vary for different drugs in different cells.
Dose-dependent topological progression of DNA hypomethylation correlates with cytotoxicity
The effect of the drugs can be perceived as a reduction in the MeC signal, with a similar effect in both cell systems, when compared to nuclei of untreated cells. In case of each drug, we observed a dose-dependent reduction of the MeC-specific signal. At lower drug concentrations (ZEB: 8 μM and 40 μM; AZA: 0.5 μM and 1 μM) the nucleus still shows significant DNA methylation in its periphery, which becomes hypomethylated at medium to higher drug doses (ZEB: 200–1000 μM, AZA: 5–20 μM). This is accompanied by a decrease of DNA methylation at interior nuclear regions, gradually affecting also DAPI-dense areas that are attributed to heterochromatin. Zebularine at the 1000 μM dose shows extremely strong hypomethylation in the entire nuclear space, including a large portion of heterochromatin in the nuclear interior (Figure5). In comparison, AZA shows similar effects already at 5 μM (data not shown). These observations support our findings presented in Figure3. The visual impressions of DNA hypomethylation in response to drug type and concentration were confirmed by quantitation of MeC and DAPI signal codistributions in the respective nuclei and displayed as accompanying scatter plots (Figure6).
MeC/DAPI codistribution patterns are independent from cell cycle interphases
Analysis of DNA methylation levels in repeat sequences correlates with imaging results
Correlation between imaging and sequence-based methylcytosine levels
Normalized MeC intensity
Normalized Alu PMR value
Normalized Sat2 PMR value
Normalized Satα PMR value
Correlation coefficient R*
Epigenetic drugs including DNA methyltransferase inhibitors, which are meant to correct for DNA methylation imbalances in cells, constitute promising therapeutic approaches in the battle against cancer. The FDA-approved azanucleotides 5-azacytidine and decitabine are already administered to patients with hematologic neoplasias. Zebularine has emerged as a new member of this type of agents that has shown potentials for long-term oral applications, as a result of systematic comparative analyses[23–27, 70, 71]. However, most of the assessments have been performed utilizing molecular methods that reveal precise information regarding CpG methylation profiles of non-repetitive sequences, but are currently costly and time-consuming, if not challenged, when applied in a cell-by-cell mode. Nevertheless, we believe that analysis of cultured cell models at single-cell resolution is necessary to obtain a more global and cell systemic picture of drug action and efficacy in the search for new drugs as well as the epigenetic evaluation of existing drugs. Thus, high-content and high-throughput analyses, which have been supported by recent advancements in imaging technology and computational capacities, offer valuable means for rapid and cost-effective cellular phenotyping in drug screening. Furthermore, the vast majority of studies so far have been focusing on assessing the hypomethylating potential of drugs on selected gene promoters in combination with cell viability testing for drug cytotoxicity and genotoxicity. However, hypomethylating agents can also perturb the epigenetic regulation of chromatin conformation, thus having an impact on the higher-order genome organization and nuclear architecture that regulate genome integrity and gene expression. We were interested in tracking the progression and extent of such global structural changes, also in correlation with drug cytotoxicity to additionally elaborate on the verification of the 3D-qDMI system’s utility for the therapeutic field. Towards this end, we have conducted a comparative cell-by-cell evaluation of zebularine and its extensively characterized isoform 5-azacytidine based on their effects on global nuclear DNA and its higher-order organization in the cell nucleus. For the purpose of generating comparable topological data, we chose human cell culture models that have rendered themselves as sensitive to both agents, as well as cell culture conditions and drug doses that have been used previously in comprehensive studies to explore differential changes on the level of DNA methylation for targeted single-copy CpG sites. Our study includes standard viability testing for measuring cytotoxicity and upgraded 3D-qDMI for evaluating the demethylation effects on two levels: (i) changes in the load of nuclear MeC (I MeC), and (ii) alterations in the spatial codistribution of MeC and global DNA, including condensed heterochromatin regions that are represented by bright DAPI areas in the nuclei of cells. Our cytotoxicity data as well as the results of our topologic approach are strongly concordant with data presented by other investigators[23, 25, 26, 73–75]. Drug response efficacy, as judged by the degree of spatial nuclear MeC/DAPI patterns, was comparably high for the two drugs across all concentrations.
In terms of cytotoxicity, we found that the Huh-7 hepatocarcinoma cells reacted more sensitively to zebularine than the prostate cancer cells. Nevertheless, for both cell types, zebularine elicited similar cytotoxicity levels at doses that were one to two orders of magnitude higher than for 5-azacytidine, thus can be considered as much less cytotoxic at near-equimolar concentrations. The results are in accordance with data from other investigations that have probed the two agents in various other cancer cell models such as bladder (T24), colon (HCT-116), ovarian (A2780 and HEY) and breast (MBA-MD-231 and MCF-7) cancer cell lines, as well as in acute myeloid leukemia cells (AML 193)[23, 25, 73–75]. Investigations addressing the chemistry behind this phenomenon have led to cumulative evidence indicating the formation of a permanent covalent bond between human as well as selected bacterial DNMTs and 5-azacytidine that can trap the enzyme in a suicide complex (triggering apoptosis). In comparison, only a stable but no permanent covalent bond has been proven between zebularine and the same DNMTs, which would allow the enzymes’ release after binding in vitro as well as in vivo. This may explain why higher concentrations of zebularine are necessary for similar levels of global DNA hypomethylation in cell nuclei and its lower cytotoxicity (at equimolar concentrations), compared with AZA[76, 77].
Furthermore, we observed that the increase in cytotoxicity correlates with global 5-methylcytosine levels, especially the extent of DNA hypomethylation at DAPI-positive heterochromatic sites as revealed by 3D-qDMI through scatter plotting of MeC/DAPI codistribution. This was also true for AZA-treated cells (data not shown). Along the same lines, when localizing low-intensity MeC and DAPI sites in the same nuclei, we could map the gradual increase in LIMs from the nuclear periphery into the more interior parts of the nuclei. However, we experienced that a strong level of LID increase within the nuclei interior was already seen at the lower zebularine concentration (8–40 μM), compared to naïve cells, which did not significantly change up to the highest concentration applied (1000 μM). These LID-patterns were very similar to the one in AZA-treated cells (Figure8), in which the majority of LIDs were found to be located in the nuclear periphery. These conclusions are drawn from images of cells with seemingly intact nuclear envelope. In fact, for drug concentrations ≥5 μM for 5-azacytidine and ≥500 μM for zebularine, a large number of cells were found to present DAPI and MeC signals outside of their nuclei, leading to the assumption that the drugs had also affected the nuclear envelope and caused DNA leakage. In these cells the respective LID curves were located below the diagonal of the graphs (not shown). Due to the cytotoxic effect induced by high drug concentrations, such cells were not included in our further analyses.
Therefore we cannot exclude any contribution of topological changes of gDNA/heterochromatin to cytotoxicity. On the contrary, we assume that global DNA demethylation may lead to both DNA hypomethylation as well as gDNA reorganization, which are bilateral and together could lead to cellular decline. Although, our data here suggest that cytotoxicity is more fine-correlated with DNA hypomethylation than with bulk DNA reorganization. However, it may also be possible that only local gDNA rearrangements occurred under the conditions applied in our study. The latter effect is conceivable from the increase of LIMs in nuclear areas that harbor heterochromatin: as a significant LIM increase was detected for cells already at low zebularine doses, a compounding of both DNA demethylation effects may have triggered cellular disruption. Figure6 underlines the fact that 5-azacytidine has equivalent effects at concentrations that are much lower than of zebularine.
The mode of action of azanucleosides is quite complex. Cytosine hypomethylation by azanucleosides, including zebularine, has been extensively reported to reactivate tumor suppressor genes and apoptosis-related genes[79–81] but also the relaxation of highly compacted chromatin that can be seen as a loss of gDNA (DAPI) signal per voxel[43, 44], as chromatin conformation is linked to DNA methylation and its bilateral relationship to histone tail modifications. Therefore, we believe that cell-by-cell topological analysis as used in our approach, i.e. the topology of LIMs and LIDs in combination with the display of differential MeC/DAPI colocalization patterns shows a potential to serve as a valuable indicator for the observed phenomena: cytotoxicity-correlated global DNA hypomethylation and DNA reorganization, as consequences of drug effects. For the selected combinations of cell types and agents, the measurement of mean MeC signal (I MeC) — a derivative of DNA methylation load, across all imaged cells — corresponded well with the level of cytotoxicity (Figure4). However, for the majority of cases I MeC presented a relatively high standard deviation, whereas for the same cell populations we observed a low fraction of dissimilar cells in terms of MeC/gDNA distribution (Figure5). The discrepancy between the two signatures becomes more plausible with the analysis of synchronized DU145 cells: high similarity was measured between G0/G1-cells and G2-cells in MeC/DAPI codistribution (Figure10). On the contrary, individual intensity values for global 5-methylcytosine (MeC) and overall DNA (DAPI) nearly doubled between G0/G1-phase and G2-phase as expected, although with a large spread in both signal distributions indicating high signal variability even in synchronized cells (Figure11). Based on these findings, we believe that signatures based on spatial MeC/DAPI codistribution are more robust in MeC-phenotyping of cells than simply measuring DNA methylation loads, as they can better distinguish between drug-induced demethylation effects and the variation of methylation among individual cells. In combination with K-L divergence measurement, such a cell-by-cell cross-examination as performed with 3D-qDMI can provide structure-based quantities for studying epigenetic drug response.
Finally, in order to test the quantitative accuracy of 3D-qDMI a comparative analysis was performed utilizing MethyLight assays that have been specifically designed for and proven to measure differential levels of DNA methylation in repeat sequences such as Alu, Sat2, and Satα with high confidence. These sequences are highly methylated in human cells and also represent a significant portion of their genomes. Therefore, they have been proven to serve as surrogates for measuring the global content of 5-methylcytosine in cells. Our comparative analyses revealed a significantly high degree of correlation between the outcomes of the two methods. We chose MethyLight as a validated technique over high-pressure liquid chromatography (HPLC), used as a standard method for measuring global DNA methylation: as the latter method requires significantly more input DNA (5–10 μg).
We conclude that the results of our work strongly support the idea of utilizing the spatial higher-order genome organization as a sentinel for drug-induced toxicity effects in liaison with global DNA hypomethylation. In particular, nuclear DNA methylation distribution patterns have proven to serve as an indicator of topological changes of the genome that could perturb spatial interactions of genomic loci and subsequent expression programs leading to cytotoxicity in treated cells. This is quite conceivable as it has been observed that DNA hypomethylation after treatment with DNMTi can be accompanied by additional changes in histone-tail modifications and nucleosome depletion that decrease DNA-repressive mechanisms and support a more open chromatin conformation[83–86], an effect that we could reconcile with 3D image analysis for H3K9me3. A decrease in this repressive and compacting chromatin landmark with increasing doses of 5-azacytidine correlates well with a decrease in gDNA signal, and could be interpreted as chromatin decondensation (Figure7). These downstream effects remain to be evaluated by determining the underlying molecular effects of possible cellular reprogramming, including the degree of heterochromatin demethylation. Especially, the loss of global DNA methylation at heterochromatic areas of the genome that harbor highly repetitive DNA sequences such as highly abundant Alu repeats, transposable long interspersed nuclear elements (LINEs) and satellite DNAs can be associated with multiple risks towards genome instability[8, 88]; through an adverse reorganization of the genome with side effects, such as transcriptional activation of oncogenes, activation of latent retrotransposons, chromosomal instability, and telomere elongation of chromosomes[11, 89–92]. More specifically, Satα and Sat2 DNA hypomethylation may favor centromeric and pericentromeric instability, respectively. Alu retroelements, if left unchecked, would insert throughout the genome into non-coding and coding regions. The result would be mutations, and activation of oncogenes: spontaneous insertion of an Alu element causes nearby promoters to be hypomethylated, increasing gene expression[93, 94]. Diseases directly associated with Alu insertion into coding regions include neurofibromatosis, haemophilia, agammaglobulinaemia, leukemia, breast cancer and ovarian cancer. Any malignancy caused by Alu insertion is both heritable along somatic cell lines as well as in the germline. This concern has been recently strengthened by observations, in which specific genomic areas were found to become re-methylated during a following DNA replication step after initial drug-induced demethylation; as a possible mechanism to protect these sequences from permanent hypomethylation. The study showed that exposure of cancer cells to agents such as 5-azacytidine and decitabine preferentially led to demethylation of CpGs not located in CpG-islands, whereas island-associated CpGs became preferentially re-methylated, suggesting that CG-dinucleotides in repetitive elements could become more persistently hypomethylated than gene-associated CGs.
In light of these observations, it appears reasonable to point out the necessity of new assays and complementary bioinformatics for detecting unwanted genomic-scale adverse effects such as heterochromatin reorganization, that could be used as endpoints in the cytotoxic and genotoxic risk assessment of already existing demethylating drugs and next-generation chromatin-targeting agents under development. Recent advancements in cellular imaging and computational image analysis have made it feasible for large volumes of images from thousands of cells to be analyzed in relatively short amount of time at substantially lower costs. Imaging-based cytomics also enables the quantification of spatial and temporal distribution of molecules and cellular components within their native environment, which can boost understanding drug activity at the cell systemic level. Within this context, MeC phenotyping appears to provide a valuable technology, and further investigations will be crucial to evaluate its performance for a broader spectrum of epigenetic drugs in cytotoxicity and eventually genotoxicity testing. Hence, the combination of 3D-qDMI with comparative techniques that provide genome-wide sequence-specific MeC-profiles and detail concurrent changes in chromatin conformation could lead to validation of MeC phenotypes in assessment of drug-induced chromatin states. A variety of impressive high-resolution sequencing-based techniques have recently become available such as NOMe-Seq, which provides nucleosome positioning landscapes; chromosome conformation capture (3C) methodology and its whole-genomic version Hi-C, which map the 3D architecture of the genome by proximity-based ligation and subsequent next-generation sequencing[98, 99]; a related method called chromatin interaction analysis using paired-end tag sequencing (ChIA–PET), and newer attempts that focus on increasing the sensitivity of chromatin immunoprecipitation-based assays towards single-cell analysis. For example: the correlation of chromatin textures derived from MeC patterns with matching nucleosome depleted regions and proximity-ligation profiles can lead to the identification of MeC phenotypes indicative of risky and genotoxic drug effects.
Cedars-Sinai Medical Center
Fetal bovine serum
- IC10 :
Inhibitory concentration at which 10% of cells are nonviable.
We thank Patricia Lin (CSMC Research Flow Cytometry Core) for helping us with flow cytometry and Vaithilingaraja Arumugaswami (CSMC) for Huh-7 cells. This work was supported by the DOD-CDMRP Award W81XWH-10-1-0939 (to JT), the NIH grant 1R21CA143618-01A1 (to AG), and institutional grants from the Department of Surgery at CSMC.
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