Immortalized normal human bladder epithelial cells, TRT-HU1, were maintained as described previously¹⁹. The TRT-HU1 cell line was constructed and extensively characterized in previously published papers. Cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM), containing 10% fetal bovine serum (FBS, Invitrogen), 1% penicillin/streptomycin, and 1% L-glutamine (Sigma, St. Louis, MO) in a 37 °C humidified incubator with 5% CO₂. TRT-HU1 cells were seeded in 10 cm culture plates at a density of 1 × 10⁶ cells in standard growth medium. When the cells reached approximately 80% confluence, they were treated and incubated with 10 mM of α-OG or vehicle for 72 h. For the crystal violet staining cell proliferation assay, cells were stained with 0.5% crystal violet (Sigma-Aldrich Corp., St. Louis, MO, USA) in 30% ethanol for 10 minutes at room temperature. The cells were lysed in a 1% SDS solution. The absorbance of the solution was measured using a microplate spectrophotometer at a wavelength of 595 nm.

Methylation profiles were obtained using the Illumina Infinium HumanMethylationEPIC BeadChip kit, which assayed approximately 850,000 methylation sites per sample at a single nucleotide resolution²⁰. Methylation scores were computed as β-values, which took into account the ratio of methylated probe intensities and the overall probe intensities (methylated and un-methylated plus a constant, C = 100). β-values are between 0 and 1. Assays and validations were performed according to the manufacturer’s recommendations.

A data analysis pipeline was established using a combination of R Studio and Bioconductor. Illumina HumanMethylationEPIC data (IDAT files) were imported into the Bionconductor minfi package. Extension of minifi package to support EPIC arrays is described in previous literature²¹. Background in the data was corrected using PreprocessNoob²². No normalization was done. Data was mapped to the genome according to standards outlined by minfi. Annotations were added using IlluminaMethylationManifest, a class built within the minfi package. Volcano plots were constructed using the Biconductor package, TCGAbiolinks²³. Heatmaps were created using the Bioconductor package, ComplexHeatmap²⁴. Differentially methylated genes (DMGs) were identified using a simple T-test comparing treated and un-treated groups. Additionally, we compared the mean β-values of two groups and only included probes that had a difference of 10%. Using the DAVID software (Ver. 6.8)²⁵, we performed functional enrichment analysis of the DMGs to identify cellular processes and pathways perturbed by α-OG treatment.

From the functional enrichment analysis, we identified the hypo-methylated genes as those involved in cellular processes, including cell-cell adhesion and chromatin remodeling. We then searched for interactions among the hypo-methylated genes using the STRING database²⁶. A network model was reconstructed with the interactions between these genes and visualized using Cytoscape (Ver. 3.4)²⁷. Node size represents degree centrality, which is the number of interactions in the network model, and edge thickness represents interaction scores, which are combined scores obtained from the STRING database²⁶. These combined scores were computed by adding the probabilities from different evidence of interactions in the database and correcting for the probability of randomly observing an interaction.

Total RNA was purified using the MagNA Pure Compact RNA isolation kit, according to the manufacturer’s instructions (Roche). cDNA was synthesized using the iScript cDNA Synthesis Kit (Bio-Rad). Q-PCR was carried out with iTaq universal SYBR green supermix (BioRad) on a 7500 Fast Real-Time PCR system (Life Technologies). The annealing temperature for the qPCR was set to 60 °C and the total cycle number was 40. Actb was used as internal control for gene expression normalization. Primers used for qRT-PCR assay are described in Supplementary Table 1.

Total cell lysates were prepared in lysis buffer (Bio-Rad) with protease inhibitors (Thermo Fisher). Protein levels were measured and 25 μg of cell lysates per condition were used for SDS-PAGE gel running. After transferring proteins to nitrocellulose membranes, western blot analysis was performed using antibodies specific for p53 (1:1000; sc-126; Santa Cruz), p21 (1:1000; 2947;Cell Signaling Technology), JunB (1:1000; 3746; Cell Signaling Technology), ARID1A (1:1000; 12354; Cell Signaling Technology), HDAC4 (1:1000; 5392; Cell Signaling Technology), PKD (1:1000; 2052; Cell Signaling Technology), β-catenin (1:1000; 8480; Cell Signaling Technology), PBRM1 (1:1000; 91894; Cell Signaling Technology), SMARCA2 (1:1000; 11966; Cell Signaling Technology), and β-actin (1:2000; A1978; Sigma-Aldrich). These were incubated overnight and followed by anti-specie-specific HRP-conjugated secondary antibodies (1:5000; 7074, 7076; Cell Signaling Technology) and then chemiluminescent detection. Some blots were stripped using Restore (Thermo Fisher) and detected using other primary antibodies.

Cells were seeded 24 h before experiments and incubated with α-OG-containing media for 20 h. A commercially available EpiQuik™ DNMT Activity/Inhibition Assay Ultra Kit (Epigentek, Farmingdale) was used to determine DNMT enzymatic activity as per the manufacturer’s instruction. For the TET activity assay, the Epigenase^TM 5mC-Hydroxylase TET Activity/Inhibition Assay Kit (Colorimetric) was used, as per the manufacturer’s instructions. This sandwich-based 5hmC ELISA reads the conversion of methylated products to hydroxymethylated products through the presence of TET enzymes in samples.

The Ethics Committee of Ewha Womans University Hospital (Seoul, Republic of Korea) approved this study. The Institutional Review Board of Ewha University Hospital approved collection, curation and analysis of all samples. All subjects participated in this study provided written informed consent, and all experiments were performed in accordance with relevant guidelines and regulations.

Subjects, including IC patients (mean age, 52.5 ± 10.1) and healthy controls (mean age, 54.2 ± 9.3), were Asian-descent female residents in South Korea who were enrolled at their initial evaluation, before any treatments or procedures. They were diagnosed and recruited by two independent urologists, Drs. Hana Yoon and Hyun Seok Yoon, who have extensive clinical expertise in IC at an outpatient urology clinic at Ewha Womans University Hospital. Careful clinical diagnosis was done using clinical criteria in the AUA guidelines^28,29; “An unpleasant sensation (pain, pressure, discomfort) perceived to be related to the urinary bladder, associated with lower urinary tract symptom(s) of more than 6 weeks duration, in the absence of infection or other identifiable causes” (http://www.auanet.org/education/guidelines/ic-bladder-pain-syndrome.cfm). Diagnostic criteria included persistent or recurrent chronic pelvic pain, pressure or discomfort perceived to be related to the urinary bladder accompanied by at least one other urinary symptom such as an urgent need to void or urinary frequency in the absence of any identifiable pathology. Work-up included symptom assessment, cystoscopic evaluation, physical examination, urodynamics, and/or urine culture. Patients with a history of other diseases (such as any types of cancer, inflammation, or diabetes, etc.) were excluded. Patients who were under any active treatment or medication were clearly excluded. Only subjects >2 months “free of treatment, therapy, or any medications”, such as hormone use, pentosan polysulphate, or intravesical instillation therapy, were included. Staging was done based on symptoms, bladder pain, and quality of life. Matched controls were carefully selected considering age, menopausal status, hormone use et al. Bladder biopsies were performed before procedures such as hydrodistention or fulguration. Biopsy sites included lateral walls, dome, posterior wall of bladder wall, but not from trigone, for both IC patients and controls.

IHC analysis for ARID1A expression was performed on 5-μm slides using a polyclonal rabbit anti-ARID1A antibody (1:250, HPA005456; Sigma-Aldrich). Antigen retrieval was performed by submerging the tissue sections in citrate buffer (pH 6.0) and then in a steamer for 10 minutes. The sections were then incubated with the rabbit antibody at a dilution of 1:200 at 4 °C overnight. A positive reaction was detected by the EnVision + System (Dako).

All data were generated from experiments performed at least three times and expressed as mean ± standard deviation (SD). The student’s t-tests were used to determine the statistical significance of differences between samples treated under different conditions. Differences were considered statistically significant when p < 0.05 (*), p < 0.01 (**), or p < 0.001(***).

In light of our previous global metabolomics data linking α-OG to cell cycle arrest and proliferation suppression¹⁶, we first investigated the effects of α-OG in immortalized normal bladder epithelial cells. Cell cycle transition and proliferation were measured in TRT-HU1 cells treated with or without 10 mM of α-OG. Consistent with previous reports, we observed significant suppression of cell proliferation in response to α-OG (Fig. 1A). Western blot analysis was performed to ascertain the involvement of several key cell cycle and proliferation regulators. We found that levels of p53 and p21 significantly increased while levels of JunB modestly increased in the presence of α-OG (Fig. 1B).Figure 1

Cell proliferation was suppressed in response to α-OG treatment. (A) TRT-HU1, immortalized normal bladder epithelial cells were treated with 10 mM of α-OG for 72 h and then proliferation assay was performed as described in Methods. *P < 0.05 (two-sided Student’s t-test) compared with the control group. (B) Representative western blot showed the reduced levels of p53 and p21 expression in TRT-HU1 cells treated with α-OG. β-actin was used for protein normalization.

Given previous reports demonstrating that α-OG modulates epigenetic regulation, we next tested our hypothesis that the global DNA methylome is altered in response to α-OG in immortalized normal human bladder epithelial cells¹⁸. In order to assess whether the DNA methylome is changed by α-OG, EPIC array was performed. Our workflow is described in Fig. 2. Our analysis and data requisition resulted in differentially methylated genes (DMGs) in response to α-OG (Supplementary Table 2–4).Figure 2

Experimental scheme describing EPIC DNA methylation profiling and the following bioinformatics analysis.

In order to explore the contribution of DNA methylation signatures in IC, we performed functional enrichment analysis and network modeling on the DMGs. Enriched cellular processes and biological pathways perturbed by α-OG treatment were identified by using DAVID software²⁵. Hypo-methylated genes were enriched for cell-cell adhesion, cell projection organization, neuron projection development, cell cycle processes, chromatin remodeling, and Rho protein signal transduction regulation, while cellular responses to stress, Ras GTPase activity, and transport of NADH to uniquitinone in the mitochondrial electron transport chain were enriched for by hyper-methylated genes (Fig. 4A). We also found that KEGG pathways. inositol phosphate metabolism, glycosylphosphatidylinositol-anchor biosynthesis, leukocyte trans-endothelial migration, phosphatidylinositol signaling were enriched for by hypo-methylated genes and endocytosis, Alzheimer’s disease, oxidative phosphorylation, Huntington’s disease were enriched for by hyper-methylated genes (Fig. 4B). Table 1 shows the related DMGs for each of the enriched cellular processes.Figure 4

Enriched biology perturbed by α-oxoglutarate. (A and B) Enriched cellular processes (A) and KEGG pathways (B). Bar plot represents scores of enrichments by hyper- and hypo-methylated genes. (C) Network model describes cell-cell adhesion and chromatin remodeling genes that were hypo-methylated by α-OG treatment.

ARID1A, HDAC4, PKD1, β-CATENIN, SMARCA2, and PBRM1 were suggested in our network model for IC and were selected for further validation. These genes were all hypo-methylated in response to α-OG treatment. To ascertain that α-OG treatment modifies the DNA methylome in TRT-HU1 cells, we next quantified the levels of DNA methylation and gene expression of the targeted candidate genes. Using quantitative RT-PCR analysis with customized primers (Supplementary Table 1), we found the mRNA expression levels of all candidate genes as being slightly elevated. Gene expression of ARID1A was significantly increased in the α-OG treated condition (p = 0.018) (Fig. 5A). The Protein expression levels of ARID1A and SMARCA2 increased; however, those of HDAC4, PDK, β-CATENNIN, and PBRM1 did not (Fig. 5B).Figure 5

The expression levels of ARID1A were significantly increased in α-OG treated condition. (A) Quantification result from RT-PCR analysis to measure the gene expression levels of six candidate genes (ARID1A, HDAC4, PKD1, β-CATENIN, SMARCA2, and PBRM1) in the presence or absence of α-OG. *P < 0.05 (two-sided Student’s t-test). (B) Representative western blot show the levels of candidates (ARID1A, HDAC4, PKD1, β-CATENIN, SMARCA2, and PBRM1) and β-actin. (C) DNMT and (D) TET activity were measured in response to α-OG treatment. *P < 0.05 (two-sided Student’s t-test). (E) Representative Immunohistochemical stain showed ARID1A expression in bladder tissues obtained from IC patients (IC) and healthy donors (C). (F) A diagram showing the potential mechanism that redundant α-OG in urine may regulate bladder epithelial cells and contribute to suppression of cell proliferation.

To further elaborate on the effects of α-OG on epigenetic regulation in immortalized normal bladder epithelial cells, we measured the activity of two DNA methylation regulators, DNMT and TET, in the presence of α-OG (Fig. 5C). In our experiments, α-OG treatment suppressed TET activity almost completely; however, there was no influence on DNMT activity (Fig. 5D).

On histological examination, we found that ARID1A expression greatly increased in IC patients. IHC analysis of bladder tissue samples obtained from 10 IC patients and 10 normal controls showed 100% positive staining in IC tissue for ARID1A, while none of the control tissue showed any staining (Fig. 5E). A hypothetical diagram suggesting epigenetic modulation on ARID1A by α-OG is shown in Fig. 5F.