Renovascular disease induces functionally relevant, locus-specific alterations to DNA methylation and hydroxymethylation in swine scattered tubular-like cells

Abstract

Background:

Scattered tubular-like cells (STCs) are dedifferentiated renal tubular cells that repair other damaged kidney cells. STCs may be damaged and rendered ineffective by renovascular disease (RVD), but the underlying mechanisms remain unknown. We hypothesized that RVD induces changes in methylated (5mC) and hydroxymethylated (5hmC) DNA and modulates the transcriptomic profile and functional properties of swine STCs.

Methods:

CD24+/CD133+ STCs were harvested from pig kidneys after 10 weeks of RVD or sham (n=6 each) and their 5mC and 5hmC profiles of individual peaks were examined by immunoprecipitation sequencing (MeDIP-/hMeDIP-seq, respectively, n=3 each). Integrated (MeDIP/hMeDIPseq/mRNA-seq) analysis was performed followed by functional analysis of overlapping differentially expressed (DE) genes. STC-protective effects were assessed in vitro before and after epigenetic (Bobcat339) modulation.

Results:

MeDIP-seq analysis identified 1,362 hyper-methylated and 1,432 hypo-methylated peaks in RVD-STCs compared to Normal-STCs, which correlated with 80 upregulated and 55 downregulated genes in RVD-STCs. hMeDIP-seq revealed 1,447 hyper-hydroxymethylated and 765 hypo-hydroxymethylated peaks in RVD-STCs versus Normal-STCs, which correlated with 80 genes upregulated and 53 downregulated in RVD-STCs. Overlapping upregulated genes were mainly implicated in the regulation of oxidative phosphorylation, apoptosis, and lipid metabolism (e.g., STAT6), whereas overlapping downregulated genes were mainly involved in cell proliferation. Importantly, RVD increased STAT6 protein expression and impaired the proliferative capacity of STCs, which were partially reversed by treatment with Bobcat339, which also enhanced the ability of RVD-STCs to promote the viability of injured tubular epithelial cells.

Conclusions:

Renal ischemia induces locus-specific epigenetic alterations, associated with transcriptomic changes and impaired reparative function of swine STCs. These observations may contribute to develop novel approaches to preserve the reparative capacity of STCs in individuals with RVD.

Graphical Abstract

INTRODUCTION

Renovascular disease (RVD) is a major cause of secondary hypertension, often caused by atherosclerosis, which results from the blockage or narrowing of one or both renal arteries. RVD affects almost 7% of individuals older than 65 years (1) and is encountered incidentally in patients undergoing angiographies for peripheral vascular disease (2). Importantly, RVD can lead to chronic kidney disease and end-stage kidney failure, accounting for an important fraction of patients entering dialysis programs in the United States (3). Furthermore, these patients tend to develop renovascular hypertension, which aggravates renal injury and predisposes them to life-threatening cardiovascular complications (4). Therefore, elucidation of the mechanisms underlying renal injury in RVD is critical to prevent these complications and develop novel therapies to treat this prevalent disease.

Scattered tubular-like cells (STCs) are surviving undifferentiated renal tubular epithelial cells that co-express the cell surface markers CD24 and CD133 and acquire progenitor-like characteristics to repair other damaged renal cells (5, 6). Indeed, the number of STCs has been shown to predict tissue recovery in patients with acute tubular necrosis (7). Experimental studies have shown that exogenous delivery of STCs regenerates tubular structures and ameliorates renal dysfunction in several animal models of acute and chronic renal damage (8, 9). In line with this, we have shown that intra-renal delivery of swine STCs (10) or their STC-derived extracellular vesicles (8) improves glomerular filtration rate and decreases fibrotic and inflammatory injury in the stenotic kidney, underscoring their potential to preserve ischemic kidneys.

However, RVD may alter the endogenous characteristics and impair the reparative benefits of STCs. We have previously shown that experimental RVD induces changes in the transcriptomic profile of swine STCs (11, 12), impairing their potential to repair pig and human tubular cells in vitro (13, 14) and ischemic murine kidneys in vivo (10). We have also shown that RVD alters the global epigenomic landscape of swine STCs. Specifically, we found (15) that RVD alters the average methylation, commonly associated with transcriptional repression (16), and hydroxymethylation, often associated with transcriptional activation (17), of the carbon-5 of cytosine (5mC and 5hmC, respectively) on DNA across the entire gene body. However, whether RVD induces functionally relevant, locus-specific alterations to DNA methylation and hydroxymethylation in swine STCs, which are critical to understand the direct regulatory mechanisms of gene expression, and their reversibility with epigenetic reprogramming in vitro remains unknown.

In this study, we took advantage of DNA methylation (transcriptional repression)-, hydroxymethylation (transcriptional activation)-, and mRNA-sequencing (MeDIP, hMeDIP-seq, and mRNA-, respectively) to compare the phenotypes of STCs harvested from normal and RVD pigs. We hypothesized that RVD induces changes in individual peaks of 5mC and 5hmC DNA and modulates the transcriptomic profile and functional properties of swine STCs.

METHODS

STCs were harvested from pig kidneys after 10 weeks of RVD or sham (n=6 each) and their 5mC and 5hmC profiles of individual peaks were examined by immunoprecipitation sequencing (MeDIP-/hMeDIP-seq, respectively, n=3 each). Integrated (MeDIP/hMeDIPseq/mRNA-seq) analysis was performed followed by functional analysis of overlapping differentially expressed genes. Then, STC-protective effects were assessed in vitro before and after epigenetic modulation.

Animal studies

Animal studies were approved by the Mayo Clinic Animal Care and Use Committee (Alfonso Eirin Massat A00006848–22). Twelve juvenile domestic pigs (Sus Scrofa Domesticus, Manthei Hog Farm, Elk River, MN, USA) were studied for 10 weeks at our AAALAC accredited animal facilities. At baseline, pigs were anesthetized with intramuscular tiletamine hydrochloride/zolazepam hydrochloride (5mg/kg, Telazol^®, Fort Dodge Animal Health, New York, NY, USA) and xylazine (2mg/kg), and anesthesia maintained with ketamine (0.2mg/kg/min) and xylazine (0.03mg/kg/min). Unilateral RVD was induced in 6 pigs by placing a local irritant coil in one of the main renal arteries using fluoroscopy (18–20), whereas a sham procedure, including fluoroscopy without placement of an irritant coil, was performed in the remaining 6 pigs. Animals were then allowed to recover and transferred to our institutional housing facilities.

Ten weeks after the induction of RVD or Sham, pigs were similarly anesthetized, intubated, and mechanically ventilated. Under sterile conditions, a vascular cut-down was performed to place vascular sheaths in the carotid artery and external jugular vein. A 7F arterial guide was also advanced to the renal arteries using fluoroscopy and the degree of stenosis was assessed by renal angiography. Single kidney volume, perfusion, renal blood flow (RBF), and glomerular filtration rate (GFR) were determined using multi-detector computed tomography (MDCT), as previously described (21, 22). MDCT data were analyzed using Analyze (Biomedical Imaging Resource, Mayo Clinic, Rochester, MN, USA) and MATLAB 7.10 (MathWorks). An intra-arterial catheter was used to measure blood pressure, whereas systemic blood samples were collected to measure serum creatinine levels (Gamma-Coat kit; DiaSorin, Stillwater, MN).

Three days after completion of MDCT studies, pigs were euthanized with 100mg/kg IV of sodium pentobarbital (Fatal-Plus, Vortech Pharmaceuticals, Dearborn, MI). The kidneys were harvested and dissected, and STCs isolated, characterized, and cultured. In randomly selected normal and RVD pigs (n=3 each) STC DNA was collected for MeDIP- and hMeDIP-seq studies, and RNA for mRNA-seq studies.

STC isolation and characterization

TCs were isolated from the porcine renal cortex and medulla as previously described (11–14, 23). Kidney tissue was washed with 5 mL of phosphate-buffered saline, finely minced, and digested with 2 mg/mL collagenase for 1 hour. The fibrous fraction was removed using a 60-mesh stainless steel filter (250 μm), followed by further processing through a 100 μm cell strainer (24). STCs were cultured in Medium 199 supplemented with 3% fetal bovine serum (Gibco BRL, Waltham, MA) at 37°C in a humidified atmosphere containing 5% CO₂ (25). Culture medium was replaced every 48 hours to eliminate non-adherent cells. After two weeks, adherent cells were detached using trypsin (TrypLE^™ Express, Gibco BRL, Waltham, MA) and passaged (13). In vitro characterization by flow cytometry and immunofluorescence confirmed strong co-expression of the STC surface markers CD24 and CD133, with a purity exceeding 99%, consistent with previous reports (11–14, 23, 26).

MeDIP- and hMeDIP-seq

MeDIP-seq and hMeDIP-seq were performed at the Mayo Clinic Epigenomics Core as previously described (15, 26–29). Genomic DNA was extracted from STCs using the DNeasy Blood & Tissue Kit (Qiagen, Cat. 69504) and quantified with a NanoDrop spectrophotometer. DNA was diluted in TE buffer to a final concentration of 100 ng/μL and sheared using a Bioruptor^® Pico sonication system (Diagenode, Seraing, Belgium) for 7–10 cycles of 30 seconds on and 30 seconds off. Fragment size distribution was assessed using an NGS Fragment Analysis Kit (Advanced Analytical Technologies, Cat. DNF-486, Ankeny, IA). DNA fragments averaging ~200 bp were denatured at 95°C for 10 minutes.

For immunoprecipitation, 2.5–5 μg of denatured DNA in 1× DIP buffer (10 mM sodium phosphate, pH 7.0; 140 mM NaCl; 0.05% Triton X-100) was incubated with 1 μg of anti-5-methylcytosine or anti-5-hydroxymethylcytosine antibodies (Diagenode, Cat. C15200081, clone 33D3; or Hybridoma clone EDL HMC 1A, Millipore, Cat. MABE1093, respectively) for 3 hours at 4°C with rotation. Protein G Dynabeads (Thermo Fisher Scientific, Cat. 10003D) were then added, and samples were incubated overnight at 4°C. Bead–antibody–DNA complexes were washed with DIP and TE buffers, and enriched DNA was eluted, purified using the ssDNA/RNA Clean & Concentrator Kit (Zymo Research, Cat. D7010) and quantified using the Qubit ssDNA High Sensitivity assay (Thermo Fisher Scientific, Cat. Q10212).

Sequencing libraries were prepared using the ACCEL-NGS^® 1S Plus DNA Library Kit (Swift Biosciences, Cat. 10024) (30) and sequenced as 51-bp paired-end reads on an Illumina HiSeq 4000 platform at the Mayo Clinic Medical Genomics Facility.

For bioinformatic analysis, paired-end sequenced FASTQ files were aligned to the pig reference genome (bowtie2 2.3.3.1) (31) and duplicates were removed using PICARD 1.67 (MarkDuplicates). Peaks were identified (MACS2) (32) and differential peak analysis performed to determine sites of differential 5mC and 5hmC coverage using the DiffBind 2.14.0 application package (33) and the HOMER 4.10 (34) peak annotation tool. Data were reported along with their magnitude of change and visualized in volcano plots (Microsoft Excel). Genomic distribution of hyper- methylated and -hydroxymethylated [log2-fold-change (RVD-STCs/Normal-STCs)≥0.5, p ≤ 0.05] and hypo- methylated and -hydroxymethylated [log2-fold-change (RVD-STCs/Normal-STCs)≤−0.5, p ≤ 0.05] peaks was expressed based on their location (exon, intron, promoter, etc.) and distance to the transcription start site (TSS).

mRNA-seq

mRNA sequencing was performed at the Mayo Clinic Genomic Analysis Core as previously described (11, 35–38). RNA sequencing libraries were prepared using the TruSeq RNA Sample Preparation Kit v2 (Illumina). Paired-end sequencing reads were processed through an established RNA-seq bioinformatics pipeline, including MAP-RSeq version 3.1.4 (39), which incorporates the fast, accurate, and splice-aware STAR aligner (40). Following alignment, gene- and exon-level expression was quantified using Subread (41), with both raw and normalized expression values adjusted by average counts per million (CPM).

Variant and transcript analyses were conducted using STAR fusion algorithms (40), GATK HaplotypeCaller (42), Haplotype caller (42), RVBoost (43), and StringTie (44) to identify single nucleotide variants (SNVs), small insertions and deletions (indels), and both known and novel gene isoforms. Differential exon usage was assessed using DEXSeq (45), and comprehensive quality control analyses were performed on the aligned reads to evaluate sequencing library quality. Final results were generated and reported by MAP-RSeq.

Differential expression analysis was performed using raw gene counts from MAP-RSeq. Genes upregulated (CPM>0.1, fold-change >1.4, p<0.05) and downregulated (CPM>0.1, fold-change <0.7, p<0.05) were identified using edgeR (46).

Integrated epigenomic/transcriptomic analysis

Integrated MeDIP/mRNA-seq and hMeDIPseq/mRNA-seq analyses, which allow identification of biological processes with concurrent epigenetic and transcriptional derangement, were performed, as previously shown (26, 28, 29). Venn diagrams were constructed using VENNY 2.1.0 to visualize overlapping upregulated genes with hypo-methylated peaks and downregulated genes with hyper-methylated peaks in the same genes. Likewise, we sought overlapping upregulated genes with hyper-hydroxymethylated peaks and downregulated peaks with hypo-hydoxymethylated peaks in RVD-STCs compared to Normal-STCs. Functional analysis of overlapping genes was performed using the Hallmark gene sets of Gene Set Enrichment Analysis (GSEA)(47), the location of their 5mC and 5hmC peaks was visualized in the Pig Sscrofa11.1 (susScr11) Genes and Transcripts feature of The Rat Genome Database (RGD) (48) and their gene expression was visualized in heat maps generated using Heatmapper (49)

STC epigenetic modulation

To establish the contribution of epigenetic changes on the transcriptomic profile and reparative function of swine STCs, Normal- and RVD-STCs (n=6 each) were treated with the epigenetic modulator Bobact339 (10μM for 24 hours, MedChemExpress, HY-111558A) (50), a small molecule inhibitor of the ten-eleven translocation (TET) methylcytosine dioxygenases enzymes, which oxidize 5mC to 5hmC (51). Protein immunoreactivity of the lipid metabolism gene signal transducer and activator of transcription 6 (STAT6), which was upregulated and exhibit hyper-hydroxymethylated peaks in RVD- compared to Normal-STCs, was assessed by immunofluorescence staining (Cell Signaling Technology, Danvers, MA, Cat# 5397S). STC metabolic and proliferative activity was assessed by MTS (CellTiter 96^® Aqueous, Non-Radioactive Cell Proliferation Assay, Promega, Madison, WI) and Ki-67 immunofluorescence staining (Abcam, ab15580, Cambridge, United Kingdom) according to the manufacturer’s protocol. STC protective effects were also evaluated by their capacity to improve viability (MTT assay, Roche Diagnostics) of pig proximal tubular epithelial cells (PK1 cells) co-incubated with 10ng/mL of tumor necrosis factor (TNF)-α and 10μM of antimycin-A (AMA), a model that mimics renal ischemic injury in-vitro (52, 53). Injured PK1 cells were co-cultured with Normal-STCs or RVD-STCs, untreated or pre-incubated with Bobact339 (10μM for 24h).

Statistical analysis

Statistical analysis was performed using BlueSky 7.0 (SAS). Results were expressed as mean ± standard deviation. The Shapiro-Wilk test was used to verify the normality of the measured parameters. Normally distributed data were compared using Student’s t-test and non-normally distributed data with the nonparametric Kruskal Wallis test. p values ≤0.05 were considered significant.

RESULTS

Systemic characteristics

The systemic characteristics and renal function of Normal and RVD pigs at 10 weeks are presented in Table 1. Body weight did not differ between the Normal and RVD pigs. All RVD pigs achieved significant and comparable degrees of stenosis. Systolic, diastolic, and mean arterial pressure, as well as serum creatinine levels, were higher in RVD compared to Normal pigs. However, stenotic-kidney RBF and GFR were lower in RVD pigs compared to Normal pigs, reflecting impaired kidney perfusion and function (54).

Table 1.

Systemic characteristic of normal sham and renovascular disease (RVD) pigs (n=6 each) at 10 weeks.

Parameter	Normal	RVD
Body Weight (Kg)	51.3 ± 2.3	51.0 ± 5.2
Degree of stenosis (%)	0	75.2 ± 6.9*
Systolic blood pressure (mmHg)	94.7 ± 3.4	144.6 ± 21.5*
Diastolic blood pressure (mmHg)	65.3 ± 7.4	119.0 ± 14.6*
Mean arterial pressure (mmHg)	75.1 ± 5.0	127.5 ± 15.9*
Serum creatinine (mg/dL)	1.2 ± 0.2	1.9 ± 0.2*
RBF (mL/min)	637.7 ± 32.5	332.7 ± 55.8*
GFR (mL/min)	97.1 ± 6.3	57.0 ± 8.6*

RBF: Renal blood flow, GFR: Glomerular filtration rate.

^*p≤0.05 vs. Normal.

RVD induces changes in 5mC and 5hmC peaks in STCs

MeDIP-seq analysis identified 1,362 hyper- and 1,432 hypo-methylated peaks, corresponding to 986 and 1,048 genes, respectively, in RVD-STCs compared to Normal-STCs (Figure 1A). Genes with hyper- and hypo-methylated peaks were primarily distributed in intergenic, exonic, and intronic regions (Figure 1B), and a large proportion of them were located relatively close to the TSS (Figure 1C).

Figure 1. RVD induces changes in individual peaks of 5-methylcytosine (5mC) DNA.

A: Volcano plot showing 1,362 hyper-methylated and 1,432 hypo-methylated peaks in DNA of RVD-STCs compared to Normal-STCs (n = 3 each). The vertical axis (y-axis) corresponds to the −log 2 (p-value) and the horizontal axis (x-axis) displays the log 2-fold change (FC, RVD-STCs/Normal-STCs) value. Peaks with higher and lower 5mC in RVD-STCs versus Normal-STCs are shown as red and blue dots, respectively, while non-significant peaks are shown as gray dots. B: Genomic location annotations of hyper- and hypo-methylated peaks. C Distribution of hyper- and hypo-methylated peaks across the gene body relative to the transcription start site (TSS).

hMeDIP-seq analysis showed 1,447 hyper- and 765 hypo-hydroxymethylated peaks, corresponding to 1,057 and 653 genes, respectively, in RVD-STCs versus Normal-STCs (Figure 2A). Genes with hyper- and hypo-hydroxymethylated genes were mainly distributed in intergenic, exonic, and intronic regions (Figure 2B), with a significant proportion located in relatively close proximity to the TSS (Figure 2C).

Figure 2. RVD induces changes in individual peaks of 5-hydroxymethylcytosine (5mC) DNA.

A: Volcano plot showing 1,447 hyper-hydroxymethylated and 765 hypo-hydroxymethylated peaks in DNA of RVD-STCs compared to Normal-STCs (n = 3 each). The vertical axis (y-axis) corresponds to the −log 2 (p-value) and the horizontal axis (x-axis) displays the log 2-fold change (FC, RVD-STCs/Normal-STCs) value. Peaks with higher and lower 5hmC in RVD-STCs versus Normal-STCs are shown as red and blue dots, respectively, while non-significant peaks are shown as gray dots. B: Genomic location annotations of hyper- and hypo-hydroxymethylated peaks. C: Distribution of hyper- and hypo-hydroxymethylated peaks across the gene body relative to the transcription start site (TSS).

RVD induces changes in gene expression in STCs

Integrated MeDIP-seq/mRNA-seq analysis revealed 80 upregulated genes with hypo-methylated peaks and 55 downregulated genes with hyper-methylated peaks (Figure 3A and Figure 4). Upregulated genes with hypo-methylated peaks are primarily implicated in oxidative phosphorylation and apoptosis, whereas downregulated genes with hyper-methylated peaks participate mainly in mechanistic target of rapamycin complex 1 (MTORC1) and myelocytomatosis (MYC) signaling (Figure 3C, E and Figure 4).

Figure 3. Integrated (MeDIP/hMeDIPseq/mRNA-seq) analysis.

A: Venn diagrams showing 80 upregulated (red) genes with hypo-methylated peaks (blue) and 55 downregulated (blue) genes with hyper-methylated peaks (red) in RVD-STCs versus Normal-STCs (n = 3 each). B: Venn diagrams showing 80 upregulated (red) genes with hyper-hydroxymethylated peaks (red) and 53 downregulated (blue) genes with hypo-hydroxymethylated peaks (blue) in RVD-STCs versus Normal-STCs (n = 3 each). Functional clustering analysis of 80 upregulated (red) genes with hypo-methylated peaks and 55 downregulated (blue) genes with hyper-methylated peaks in RVD-STCs versus Normal-STCs. D: Functional clustering analysis of 80 upregulated (red) genes with hyper-hydroxymethylated peaks and 53 downregulated (blue) genes with hypo-hydroxymethylated peaks in RVD-STCs versus Normal-STCs. E: Gene symbol and name of overlapping upregulated genes implicated in oxidative phosphorylation and apoptosis and overlapping downregulated genes involved in mammalian target of rapamycin complex 1 (MTORC1) and myelocytomatosis (MYC) signaling. F: Gene symbol and name of overlapping downregulated genes implicated in adipogenesis and oxidative phosphorylation and overlapping downregulated genes involved in MTORC1 and MYC signaling.

Figure 4. 5mC peak location and gene expression of overlapping genes.

A: Location of individual hypo-methylated peaks (left) and gene expression heat maps (right) of overlapping upregulated genes in RVD-STCs versus Normal-STCs (n=3 each) implicated in oxidative phosphorylation and apoptosis. B: Location of individual hyper-methylated peaks (left) and gene expression heat maps (right) of overlapping downregulated genes implicated in MTORC1 and MYC signaling. Red indicates higher (upregulated) expression, while blue signifies lower (downregulated) expression, and the intensity of the color shows the magnitude of the change.

Integrated hMeDIP-seq/mRNA-seq analysis identified 80 upregulated genes with hyper-hydroxymethylated peaks and 53 downregulated genes with hypo-hydroxymethylated peaks (Figure 3B and Figure 5). Upregulated genes with hyper-hydroxymethylated peaks are primarily implicated in adipogenesis and oxidative phosphorylation, whereas downregulated genes with hypo-hydroxymethylated peaks are mainly involved in MTORC1 and MYC signaling (Figure 3D, F and Figure 5).

Figure 5. 5hmC peak location and gene expression of overlapping genes.

A: Location of individual hyper-hydroxymethylated peaks (left) and gene expression heat maps (right) of overlapping upregulated genes in RVD-STCs versus Normal-STCs (n=3 each) implicated in adipogenesis and oxidative phosphorylation. B: Location of individual hypo-hydroxymethylated peaks (left) and gene expression heat maps (right) of overlapping downregulated genes implicated in MTORC1 and MYC signaling. Red indicates higher (upregulated) expression, while blue signifies lower (downregulated) expression, and the intensity of the color shows the magnitude of the change.

Epigenetic modulation restores the proliferative capacity of RVD-STCs

Immunoreactivity of the candidate lipid metabolism gene STAT6 was higher in RVD-STCs compared to Normal-STCs, in agreement with our mRNA-seq findings, but decreased in RVD-STCs co-incubated with the TET inhibitor Bobcat339 (Figure 6A, B). STC global metabolic activity, assessed by the conversion of MTS tetrazolium salt into a colored formazan product, was similar between RVD- and Normal-STCs but tended to increase in RVD-STCs co-incubated with Bobcat339 (Figure 6C). However, STC proliferative capacity that was blunted in RVD-STCs versus Normal-STCs, improved in RVD-STCs treated with Bobcat339 (Figure 6D). Normal STCs, but not RVD-STCs, improved the survival of injured PK1 cells (Figure 7). Co-incubation with Bobcat339 rescued the capacity of RVD-STCs to enhance the viability of injured PK1 cells.

Figure 6. Epigenetic modulation of RVD-STCs.

A: Normal- and RVD-STCs were treated with the epigenetic modifier Bobact339 (10μM for 24h), which prevents the conversion of 5mC into 5hmC by inhibiting the Ten-11 translocation methylcytosine dioxygenase (TET) enzymes. B: Representative images of immunofluorescence staining (original magnification: X40) for the lipid metabolism gene signal transducer and activator of transcription 6 (STAT6) and its quantification in Normal- and RVD-STCs untreated or treated with Bobcat339 (n=6 each). C: Cellular metabolic activity (MTS assay) of Normal- and RVD-STCs untreated or treated with Bobcat339 (n=3 each). D: Representative images of immunofluorescence staining (original magnification: X40) for the cell proliferation marker Ki-67 and its quantification in Normal- and RVD-STCs untreated or treated with Bobcat339 (n=6 each).

Figure 7. STC reparative capacity.

A: STC protective effects were assessed by their capacity to improve viability of proximal tubular epithelial cells (PK1 cells) co-incubated with 10ng/mL of tumor necrosis factor (TNF)-α and 10μM of antimycin-A (AMA). Injured PK1 cells were untreated or treated with Normal-STCs or RVD-STCs, untreated or pre-incubated with Bobact339 (10μM for 24h). B: TNF-α and AMA impaired the viability of swine PK1 cells, which was improved by Normal-STCs, but not by RVD-STCs. Bobcat339 improved the capacity of RVD-STCs to increase the viability of PK1 cells. *p<0.05 vs. PK1, †p<0.05 vs. PK1+TNF-α/AMA.

DISCUSSION

This study shows that experimental RVD induces site-specific epigenetic changes in genes that regulate the function of swine STCs. Specifically, we found that RVD-induced hypo-methylated and hyper-hydroxymethylated peaks were associated with transcriptional activation of genes primarily implicated in the regulation of oxidative phosphorylation, apoptosis, and lipid metabolism. In contrast, RVD-induced hyper-methylated and hypo-hydroxymethylated peaks were associated with transcriptional repression of genes mainly involved in cell proliferation, such as MTORC1 and MYC signaling. Importantly, RVD increased protein expression of the lipid metabolism gene STAT6 and impaired the capacity of STCs to proliferate, which were partly reversed in RVD-STCs treated with Bobcat339. Epigenetic modulation also improved the capacity of RVD-STCs to increase the viability of injured tubular epithelial cells. Therefore, our findings demonstrate that renal ischemia induces site-specific epigenetic alterations in STC genes, which are linked to transcriptional changes and might in turn impair their functional capacity.

STCs are dedifferentiated tubular epithelial cells that survive episodes of injury (5, 6) and acquire important reparative properties, similar to those of mesenchymal stem cells (55). We have previously shown that intra-renal delivery of swine STCs preserves the structure and function of the swine stenotic kidney (10). We have also shown that experimental RVD leads to STC activation (13). However, RVD-STCs are exposed to noxious insults, limiting their reparative properties in vitro (13) and potential to repair damaged kidneys in vivo (10).

An increasing body of evidence suggests that epigenetic modifications, such as DNA methylation or hydroxymethylation, might represent an important mechanism by which RVD compromises the integrity and function of STCs. Our previous studies have shown that RVD alters global patterns of DNA methylation and hydroxymethylation in swine STCs across the entire gene body (15). The current study expands on our previous observations, demonstrating that RVD induces functionally relevant, locus-specific alterations in the methylation and hydroxymethylation of DNA regions (peaks) in swine STCs. MeDIP-/hMeDIP-seq peak-wise analysis offers several advantages over global analysis, which is limited to assessing overall methylation and hydroxymethylation levels across the entire genome (56). Importantly, identifying specific localized regions of differential 5mC and 5hmC with high resolution is critical to understand the direct regulatory mechanisms of DNA methylation and hydroxymethylation on gene expression in swine STCs.

Our MeDIP-/hMeDIP-seq peak-wise analysis identified a substantial number of hyper- and hypo-methylated and -hydroxymethylated peaks in RVD-STCs compared to Normal-STCs, largely distributed within intergenic, exonic, and intronic regions. Intergenic regions, located between protein-coding genes, frequently contain major regulatory elements, such as enhancers, which loop DNA to bring promoters and their target genes into physical proximity (57). Likewise, the presence of 5mC and 5hmC peaks in exon and intron regions might also imply regulation of alternative splicing and gene expression (58, 59). Importantly, many of these peaks were located relatively close to the TSS. Regulatory elements, such as promoters and enhancers, bind near the TSS to regulate RNA polymerase binding and transcription initiation (60). Thus, the genomic distribution of hyper- and hypo-5mC and 5hmC peaks in RVD-STCs underscores their potential to influence the strength and range of gene regulation.

To identify biological processes with concurrent epigenetic and transcriptional derangement in RVD-STCs, we performed an unbiased integrated analysis combining MeDIP/hMeDIP-seq and mRNA-seq. Interestingly, our analysis identified a large number of upregulated genes with concurrent hypo-methylation and hyper-hydroximethylation peaks, as well as downregulated genes with coexisting hyper-methylation and hypo-hydroximethylation peaks. Therefore, our findings imply that RVD might exert locus-specific epigenetic control of transcriptional regulation in swine STCs.

Next, our gene ontology analysis showed that among overlapping upregulated genes are mRNAs relevant to regenerative functions of STCs, such as oxidative phosphorylation, apoptosis, and adipogenesis. This includes cytochrome c oxidase subunit 5B (COX5B), a key structural component of complex IV, critical for oxidative phosphorylation, the final stage of cellular respiration in mitochondria. We have previously shown that RVD induces structural and functional alterations in STC mitochondria associated with upregulation of the mitochondrial biogenesis marker peroxisome proliferator-activated receptor (PPAR)-γ coactivator (PGC)-1α (12, 13). Thus, epigenetic-induced upregulation of COX5B in RVD-STCs might indicate a post-transcriptional compensatory mechanism, as commonly observed in the presence of mitochondrial dysfunction or energy stress (61).

In addition, we found that expression of apoptotic genes, such as erb-b2 receptor tyrosine kinase 2 (ERBB2), was higher in RVD-STCs compared to Normal-STCs. Previous studies have shown that ERBB2 overexpression inhibits apoptosis by activating pro-survival pathways and interacting with cell cycle regulators (62). This is in line with our previous observation of increased global methylation of pro-apoptotic and hydroxymethylation of anti-apoptotic genes in swine STCs, associated with decreased numbers of apoptotic cells (15), and increased expression of pro-survival factors, such as dachsous cadherin-related 1 and olfactomedin 4 (11).

Similarly, overlapping upregulated genes included mRNAs implicated in adipogenesis. Among them is STAT6, which promotes adipocyte differentiation by interacting with PPAR-γ, the master regulator of adipocyte development and function (63). Accumulating evidence (64, 65) indicates that adipogenesis negatively influences renal tubular cell function by promoting inflammation, oxidative stress, and ectopic lipid accumulation, which impair tubular reabsorption and repair. In agreement, we previously showed that RVD-STCs exhibit increased expression of inflammatory genes and proteins (26), associated with mitochondrial superoxide production (13, 15).

In contrast, overlapping downregulated genes were mainly implicated in MTORC1 and MYC signaling. MTORC1 is a key regulator in cellular physiology that stimulates biosynthetic pathways, including cell growth and proliferation (66). For example, the MTORC1 pathway activators heat shock protein family D member 1 (HSPD1) and nicotinamide phosphoribosyltransferase (NAMPT) genes exhibited hypermethylated peaks and were downregulated in RVD- versus Normal-STCs. Importantly, mTORC1 localizes to the endoplasmic reticulum (ER), particularly at ER-mitochondria contact sites. ER stress inhibits mTORC1 (67), which in turn triggers mitochondrial fragmentation (68), in line with our previous observations of mitochondrial morphological abnormalities (12, 13) and ER-stress (14) in RVD-STCs.

Likewise, we found that expression of several downregulated genes with hypermethylated and hypo-hydroxymethylated peaks in RVD-STCs were implicated in MYC signaling, including the eukaryotic translation initiation factor 1A X-linked (EIF1AX) and the small nuclear ribonucleoprotein polypeptide (SNRPB2). MYC is a universal transcription amplifier that controls fundamental cell functions, particularly cell proliferation. Indeed, in vitro studies have shown that MYC depletion leads to cell-cycle arrest (69). Consistently, we found that senescence, characterized by a stable, permanent cell-cycle arrest, was higher in swine RVD- versus Normal-STCs (10). Moreover, in this study, we found that cell proliferation was lower in RVD- compared to Normal-STCs, consistent with our previous observations (11, 13). Taken together, our findings suggest that site-specific epigenetic changes induced by renal ischemia might compromise relevant reparative functions of swine STCs.

To mechanistically interrogate the effect of epigenetic alterations on STC functional properties, we co-incubated Normal- and RVD-STCs with the TET inhibitor Bobcat339. Notably, we found that treating RVD-STCs with Bobcat339 decreased STAT6 expression. Furthermore, treatment with Bobcat339 tended to increase metabolic activity and improve the proliferative capacity of RVD-STCs, consistent with the notion that epigenetic modifications in localized regions in the genome might partly account for transcriptional and functional changes in swine STCs. Lastly, we found that co-incubation with Bobcat339 improved the capacity of RVD-STCs to increase the viability of injured tubular epithelial cells, suggesting that site-specific epigenetic changes are important determinants of the renal reparative capacity of STCs.

We acknowledge limitations to this study, including the low number of samples, related to the high costs associated with MeDIP-, hMeDIP-, and mRNA-seq studies (70), the use of juvenile pigs, the short duration of RVD, and the lack of other co-morbidities frequently associated with human RVD, such as obesity, hypercholesterolemia, insulin resistance or metabolic syndrome. The lack of these systemic stressors may mask complex epigenetic interactions occurring in a real-world clinical setting. Although epigenomic and transcriptomic profiles can be influenced by culture microenvironments (71), our Normal- and RVD-STCs were cultured homogenously to avoid this potential confounding factor. Lastly, the therapeutic effects of Bobcat339 were demonstrated exclusively in vitro. Therefore, future longitudinal studies are needed to confirm these findings in an animal model in vivo, the time course of the observed changes, and their impact on the reparative capacity of human RVD-STCs.

In summary, this study shows that RVD induces site-specific 5mC and 5hmC modifications in DNA associated with transcriptional changes and impaired proliferative and reparative capacity of swine STCs, which could be mitigated in RVD-STCs treated with a TET inhibitor. Therefore, our observations suggest that locus-specific alterations in DNA methylation and hydroxymethylation may partly underline functional deficiencies in STCs exposed to chronic renal ischemia, warranting the development of epigenetic strategies to preserve the reparative capacity of this endogenous repair system in patients with RVD.

Supplementary Material

The MeDIP-seq, hMeDIP-seq, and mRNA-seq data of each individual sample generated in this study are available online at https://figshare.com:

Supplemental File 1: MeDIP-seq: 10.6084/m9.figshare.31000123

Supplemental File 2: hMeDIP-seq: 10.6084/m9.figshare.31000132

Supplemental File 3: mRNA-seq: 10.6084/m9.figshare.31000144

New & Noteworthy.

Scattered tubular-like cells (STCs) are dedifferentiated renal tubular cells that repair other damaged kidney cells. This study shows that renovascular disease (RVD) induces site-specific 5mC and 5hmC modifications in DNA associated with transcriptional changes and impaired proliferative capacity of swine STCs, which could be mitigated in RVD-STCs treated with an epigenetic modulator. Therefore, our observations may contribute to the development of novel approaches to preserve the reparative capacity of STCs in individuals with RVD.