Diabetes Induces Aberrant DNA Methylation in the Proximal Tubules of the Kidney

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† ‡ Takeshi Marumo,* Shintaro Yagi, Wakako Kawarazaki,* Mitsuhiro Nishimoto,* Nobuhiro Ayuzawa,* Atsushi Watanabe,* Kohei Ueda,* Junichi Hirahashi,§ | ‡ † Keiichi Hishikawa, Hiroyuki Sakurai,¶ Kunio Shiota, and Toshiro Fujita*

*Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, ‡Laboratory of Cellular Biochemistry, Department of Animal Resource Sciences/Veterinary Medical Sciences, and |Department of Advanced Nephrology and Regenerative Medicine, The University of Tokyo, Tokyo, Japan; †CREST, Japan Science and Technology Agency, Tokyo, Japan; §Apheresis and Dialysis Center, School of Medicine, Keio University, Tokyo, Japan; and ¶Department of Pharmacology, School of Medicine, Kyorin University, Tokyo, Japan

ABSTRACT Epigenetic mechanisms may underlie the progression of diabetic kidney disease. Because the kidney is a heterogeneous organ with different cell types, we investigated DNA methylation status of the kidney in a cell type–specific manner. We first identified genes specifically demethylated in the normal proximal tubules obtained from control db/m mice, and next delineated the candidate disease-modifying genes bearing aberrant DNA methylation induced by diabetes using db/db mice. Genes involved in glucose metabolism, including Sglt2, Pck1,andG6pc, were selectively hypomethylated in the proximal tubules in control mice. Hnf4a, a transcription factor regulating transporters for reabsorption, was also selectively demethylated. In diabetic mice, aberrant hypomethylation of Agt, Abcc4, Cyp4a10, Glut5, and Met and hypermethylation of Kif20b, Cldn18,andSlco1a1 were observed. Time-dependent demethylation of Agt, a marker of diabetic kidney disease, was accompanied by histone modification changes. Furthermore, inhibition of DNA methyltransferase or histone deacetylase increased Agt mRNA in cultured human proximal tubular cells. Aberrant DNA methylation and concomitant changes in histone modifications and mRNA expression in the diabetic kidney were resistant to antidiabetic treatment with pioglitazone. These results suggest that an epigenetic switch involving aberrant DNA methylation causes persistent mRNA expression of select genes that may lead to phenotype changes of the proximal tubules in diabetic kidney disease.

J Am Soc Nephrol 26: 2388–2397, 2015. doi: 10.1681/ASN.2014070665

Diabetic kidney disease is the most common cause of Proximal tubule (PT) cells of the kidney actively CKD, and the number of patients with diabetic kidney contribute to glucose homeostasis by reabsorbing disease continues to increase despite improved man- glucose through the transporter Sglt2. PT cells, as agement of diabetes.1 This may stem, in part, from the only part of the kidney expressing the appro- the irreversible nature of diabetic kidney disease. Epi- priate enzymes for gluconeogenesis, such as Pck1 genetic mechanisms have been suggested to play critical roles in the persistent phenotype changes of the Received July 17, 2014. Accepted November 26, 2014. blood vessels and organs and are likely to determine 2,3 Published online ahead of print. Publication date available at the incidence of diabetes-related complications. www.jasn.org. Aberrant increase in DNA methylation of the PGC-1a gene promoter is observed in the skeletal muscle of Correspondence: Dr. Toshiro Fujita or Dr. Takeshi Marumo, Di- vision of Clinical Epigenetics, Research Center for Advanced 4 diabetic patients. DNA methylation changes of the Science and Technology, The University of Tokyo, 4-6-1 Komaba, kidney have also been observed in the parietal epi- Meguro-ku, Tokyo 153-8904, Japan. Email: Toshiro.FUJITA@ thelial cells of diabetic animals5 and in the tubular rcast.u-tokyo.ac.jp or [email protected] compartment of patients with CKD.6 Copyright © 2015 by the American Society of Nephrology

2388 ISSN : 1046-6673/2610-2388 JAmSocNephrol26: 2388–2397, 2015 www.jasn.org BASIC RESEARCH and G6pc, also generate glucose by gluconeogenesis.7 Functional (ENaC), expressed in the thick ascending limb, distal tubule, changes in the metabolism and transport are observed in the PT connecting tubule, and collecting duct, respectively, were ex- cells from an early stage in diabetes and are considered to be cluded from the PT fraction, while mRNA of Sglt2 and Pck1, critically involved in the development of diabetic kidney dis- which are known to be expressed in PT, was enriched in the ease.7,8 Epigenetic mechanisms may underlie PT-specificgene PT fraction (Figure 1, A–C). We screened for DMRs by com- expressions and phenotype changes in diabetes, but the DNA paring the DNA methylation profile of the PT cells with those methylation profile of PT cells has not been evaluated to date. of the whole kidney, liver, and cerebrum in a genome-wide Genome-wide analyses revealed that the methylation state of manner (Supplemental Figure 1).10,11 Ontology analysis of only a fraction of the CpGs in the genome changes although in genesneighboringtheDMRsrevealedthatthegenesex- theory, that of every CpG can change.9 Comparison of the DNA pressed in the kidney were significantly enriched in the genes methylation status among organs has led to the identification of associated with the hypomethylated DMRs in the PT cells differentially methylated regions (DMRs) in each organ. Such compared with other tissues (Supplemental Tables 1 and 2). DMRs underlie tissue-dependent gene expressions and are consid- We found the enrichment of genes related to mitochondrial ered to contain information about the fundamental functions of function and the brush border, such as Sglt2 (Slc5a2) and each organ.9,10 In previous studies, we identified DMRs by com- Glut5 (Slc2a5), in the genes with PT-DMRs (Supplemental paring the DNA methylation status in different organs, including Tables 3 and 4). These data suggested strict regulation of the the liver, cerebrum, and kidney.10,11 The DMRs observed in the genes involved in metabolism and glucose uptake by DNA kidney include those localized in kidney-specifictransporters,which methylation. are hypomethylated in the kidney compared with other organs. We therefore analyzed the DNA methylation status of 55 Because the kidney is a highly heterogeneous organ with representative DMRs associated with 42 genes, selected from more than a dozen different cell types, including each tubular the genes related to the kidney and metabolism, by combined component cell and interstitial and vascular cells, the DNA methylation status of the wholekidneyisasummationthemethylation status of various cell types. In the present study, to evaluate the PT-specificDNA methylation status, we purified PT cells by sorting. We first identified PT-specificDMRs by comparing the DNA methylation status of the PT cells with that of the whole kidney. Alterations in the DNA methylation induced by diabetes were next delineated by comparing the DNA methylation status of the PT cells purified from diabetic and normal mice. Although DNA methylation is usually deemed to be relatively stable, hypermethylation of PGC-1a observed in obese patients can be reversed to the level seen in nonobese individuals after weight reduction induced by bariatric surgery.12 To evaluate the revers- ibility of the DNA methylation changes in the diabetic kidney, we determined the effects of antidiabetic therapy.

RESULTS

fi Purification of PT Cells and Figure 1. Validation of sorting and PT-speci c demethylation. (A) Kidney cells ob- db/m Identification of PT-Specific DMRs tained from 8- to 10-week-old control mice were sorted into PT and non-PT fractions using Lotus tetragonolobus lectin as the marker. (B) Expression of marker PT cells were purified by sorting from the genes of thick ascending loop of Henle (NKCC2), distal tubules (NCC), and collecting kidneys of db/m mice. Analysis of mRNA duct (bENaC) in PT and non-PT fractions (n=5pergroup;*P,0.05). In this and all other expressions revealed that markers of nephron figures, error bars represent mean6SEM. (C) Expression of markers for proximal tubules segments other than PT, such as Na-K-2Cl (Sglt2 and Pck1) and for genes showing demethylation in PT fractions (n=4–6 per group; + 2 cotransporter (NKCC2), Na -Cl cotransporter *P,0.05). (D) DNA methylation levels of genes showing significant demethylation in PT (NCC), and b-epithelial sodium channel fractions determined by COBRA (n=4–6pergroup;*P,0.05).

J Am Soc Nephrol 26: 2388–2397, 2015 DNA Methylation in the Diabetic Kidney 2389 BASIC RESEARCH www.jasn.org bisulfite restriction analysis (COBRA). Hierarchical clustering of the expression and methylation levels of the DMRs located of the DNA methylation levels at these loci classified the PT outside the promoter under diabetic conditions remains to be cells and whole kidney into the same branch (Figure 2), clarified. suggesting similarity in the DNA methylation profiles between the PT cells and whole kidney. However, several CpGs Demethylation and Increased mRNA Expression of Agt exhibited significant differences in the DNA methylation in the PT status between the PT cells and whole kidney (Figure 2). Because the expression of Agt in the PT is correlated with the Such PT-specific DMRs are considered to represent charac- progression of diabetic kidney disease,18 we further extended teristic feature of the PT in the kidney. Among the PT- the analysis to the promoter region of this gene by bisulfite specific DMRs, those showing decreased methylation in sequencing. In addition to the CpG at 470 bp downstream of the PT cells contained genes that are known to be the the transcription start site (Table 1), CpGs 183 bp downstream marker genes of PT cells,7,13,14 such as Sglt2 (Slc5a2), Pck1, and 592 bp upstream from the transcription start site were also Gcnt1 (glucosaminyl [N-acetyl] transferase 1, core 2); an en- significantly demethylated (Figure 3A). In situ hybridization zyme involved in the formation of glycolipid, G6pc;and revealed that Agt mRNA was mainly expressed in the PT cells Hnf4a, a nuclear receptor. These genes were highly demethyl- of the medulla in the kidneys of control mice (Figure 3B). In ated in the PT cells, while markedly methylated in the non- diabetic mice, expression of Agt mRNA was markedly in- PT fraction (Figures 1D and 2B). As expected, mRNA creased in the PT cells in the medulla. In addition, some glo- expressions of these genes were mainly observed in the PT merular and PT cells in the cortex also stained positive for Agt cells (Figure 1C). We also found that Cyp4a10 and Cyp4a14; mRNA, although to a minor extent. These results indicate that both P450 enzymes; and Mgea5, a glycosidase that removes Agt is induced mainly in the PT cells with concomitant DNA O-GlcNAc modifications, were demethylated and their ex- demethylation in diabetes. pressions were elevated in the PT fraction. These results indicate that differential DNA methylation underlies cell-type–specific Time-Dependent Epigenetic Changes of Agt gene expressions within the kidney, just like differences among To delineate the time-dependent epigenetic changes, 5- and tissues, and that the genes described above may be expressed 8-week-old mice were analyzed. Demethylation of Agt was not under epigenetic control. apparent in the PT cells at week 5 (Figure 4A), when the blood glucose levels and body weight begin to increase (Supplemental Diabetes-Induced Changes in DNA Methylation and Figure 4), while at week 8, significant DNA demethylation was mRNA Expression observed in the diabetic kidney. These results indicate that the In the United Kingdom Prospective Diabetes Study, good demethylation process takes place after the metabolic de- glycemic control in the early stage of type 2 diabetes mellitus rangements begin to occur. In contrast, mRNA levels of Agt was associated with long-lasting beneficial effects on the risk of in the kidney were already elevated at week 5 in the diabetic microvascular disease.15 This study also suggested that de- kidney (Figure 4B). We next analyzed the histone modifica- rangements induced in the early stage of diabetes may be im- tions of H3K9 acetylation and H3K4 tri-methylation, both of portant for the development of diabetic kidney disease. In the which are associated with active transcription.26 H3K4 tri- present study, therefore, we attempted to identify genes show- methylation was recently shown to be associated with persis- ingaberrantDNAmethylationintheearlystageofdiabetic tent induction of PAI-1 in the endothelial cells in a mouse model nephropathy, before the development of any apparent histo- of streptozotocin-induced diabetes.27 Analysis of histone modifi- logic changes. We obtained PT cells from 10-week-old db/db cation by chromatin immunoprecipitation (ChIP) quantitative mice (Supplemental Figure 2) and compared the methylation PCR revealed that H3K9 acetylation of the Agt promoter was status of PT cells purified from diabetic mice with that of PT increased at both weeks 5 and 8 in the diabetic kidney, while cells purified from control animals by cluster analysis (Figure 2). H3K4 tri-methylation was not significantly enriched in the pro- PT cells obtained from the diabetic and control mice showed a moter at week 5, but increased by week 8 (Figure 4, C and D). rather similar DNA methylation patterns, but the methylation These results suggest that epigenetic changes start from H3K9 pattern significantly differed among the eight genes with po- acetylation and gradually extend to H3K4 tri-methylation tentially functional roles (Table 1, Supplemental Figure 3).16–24 and DNA demethylation in the Agt promoter in the diabetic Quantitative RT-PCR analysis demonstrated that the mRNA kidney. expressions of these genes in the PT cells were significantly different between the diabetic and control mice (Table 1, Sup- Role of Epigenetic Changes in AGT Expression in plemental Figure 3). An inverse correlation between expres- Human Renal Proximal Tubular Epithelial Cells sion and methylation was seen at these loci except for Met. Theroleofepigeneticmodification in the expression of AGT This observation is concordant with previous reports was next investigated using human renal proximal tubular indicating a generally, but not exclusively, negative correlation endothelial cells (HRPTECs). Incubation of HRPTECs with between DNA methylation and expression.10,25 Because we 5-Aza-29-deoxycytidine, a DNA methyltransferase inhibi- investigated DMRs in the promoter regions, the correlation tor, caused promoter demethylation at a CpG 367 bp

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upstream of the transcription start site and mRNA induction of AGT (Figure 5, A and B). In addition, trichostatin A, a histone deacetylase inhibitor, increased histone acetylation of the promoter region and stimulated mRNA expression (Figure 5, C and D). Pretreatment of HRPTECs with 5-Aza-29-deoxycytidine enhanced induction of Agt by trichostatin A. These results suggest that epigenetic changes are likely to play a causative role in the increased expression of Agt in the diabetic kidney. Demethylation of Agt seems to increase the basal levels of mRNA and to augment mRNA elevation in response to stimuli that induce histone acetylation in the promoter.

Resistance of DNA Methylation Changes to Antidiabetic Therapy We next investigated whether the changes in DNA methylation in the diabetic kidney were responsive to antidiabetic therapy. Pioglitazone reduces blood glucose, albuminuria, and alterations in the glomerular gene expressions in db/db mice.28 Accordingly, pioglitazone signiﬁcantly reduced the blood glucose levels and attenuated the increase in kidney weight and albumin excretion in the diabetic mice (Figure 6, A and B, Supplemental Figure 5A). In addition, pioglitazone prevented increases in the plasma levels of triglyceride and free fatty acid (Supplemental Figure 5B). Because changes in the mRNA levels of genes involved in lipid metabolism in the glomeruli are reported to be sensitive to pioglitazone,28 we next investigated the effect of pioglitazone on the proximal tubular cell expression of Acaca, an enzyme known to be involved in fatty acid synthesis. We found that the decrease in the mRNA expression levels of Acaca in the PT of diabetic mice was restored by pioglitazone (Supplemental Figure 5C). However, induction of Agt mRNA and demethylation of promoter DNA in the PT cells were not prevented by pioglitazone treatment. Aberrant DNA methylation, including demethylation of Abcc4 as well as increase in the methylations of Slco1a1 (Figure 6, C and D) and Cldn18 (Supplemental Figure 5D), and the corresponding mRNA changes of Abcc4 and Slco1a1 were also not inhibited by pioglitazone treatment. Changes in histone H3K9 acetylation and H3K4 tri-methylation were also resistant to pioglitazone treatment (Supplemental Figure 6).

DISCUSSION

DNA methylation studies in the diabetic kidney are rather limited compared with those of other tissues affected by

regions of 42 genes identiﬁed by the D-REAM assay, are indicated Figure 2. DMRs analyzed by COBRA. Hierarchical clustering with in the grayed scale showing DNA methylation levels from 0% to Euclidean distance of DNA methylation levels determined by 100%. The loci exhibiting signiﬁcantly different values between the COBRA. The mean DNA methylation levels of the biologically PT cells (db/m) and the whole kidney (P,0.05) are indicated with triplicated samples at 55 loci, which are located in the promoter asterisks.

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Table 1. Genes with aberrant DNA methylation and their potential function Difference in Fold Change Gene CpG Site (mm9) Methylation of mRNA Gene Name Function (db/db2db/m)(%) (Diabetes/Control) Abcc4 chr14:119104200 211.3 2.22 ATP-binding cassette, Transports cAMP and drugs16 subfamily C member 4 Agt chr8:127093137 27.7 3.65 Angiotensinogen May regulate BP and/or mediate kidney injury17,18 Cyp4a10 chr4:115191979 26.8 1.90 Cytochrome P450, family 4, Regulates ENaC activities and BP19 subfamily A, polypeptide 10 Met chr6:17438506 28.2 0.34 Met proto-oncogene HGF/met protects against diabetic (HGF receptor) nephropathy20 Slc2a5 chr4:149493684 25.0 1.93 Solute carrier family 2 Reabsorbs fructose in proximal member 5 (Glut5) tubules21 Cldn18 chr9:99609027 26.1 ND Claudin 18 Involved in tight-junction epithelial paracellular barrier22 Kif20b chr19:34995181 8.1 0.70 Kinesin family member 20B Involved in mitosis and cell migration23 Slco1a1 chr6:141895886 11.3 0.11 Solute carrier organic anion Transports wide variety of anionic, transporter family, cationic, zwitterionic, and neutral member 1a1 chemicals24 Genes with differentially methylated CpG sites in the PTs between the control and diabetic mice. The percentage DNA methylation in the PT in db/db mice was subtracted from that in db/m mice. For comparison of mRNA levels in the PT, the fold change of mRNA levels between db/m and db/db mice was calculated. Mean values are shown. SEM values are presented in Supplemental Figure 3. ND, not detected.

diabetes, such as the skeletal muscle,4,12 liver,25 and pancreatic handling of glucose in the PT, but the functional role remains islets,29 even though kidney disease is a serious complication to be precisely determined. of diabetes. This is partly because changes in the DNA meth- By comparing the DNA methylation status of the sorted PT, ylation status of the whole kidney are a summation of the we identified genes bearing aberrant DNA methylation that changes in the component cell populations and the actual can potentially modify the progression of diabetic kidney methylation changes in individual cell types. To circumvent disease. Met, which encodes the hepatocyte growth factor re- this problem, we collected PTs and first characterized the DNA ceptor, is downregulated in the diabetic kidney.32 Decreased methylation status in the PTs of normal mice. We revealed Met levels with altered DNA methylation may contribute to many functionally important genes that are demethylated in kidney injury because stimulation of HGF signaling reduces the PT. Hypomethylation of Sglt2, Pck1,andG6pc and pre- interstitial fibrotic changes in the diabetic kidney.20 Persistent dominant expressions of their mRNAs in the PT indicates that changes in mRNA levels with altered DNA methylation of DNA methylation underlies selective glucose handling by the Abcc4, which is involved in the urinary excretion of drugs PT in the kidney. In addition to glucose, PT cells also reabsorb such as furosemide and thiazides,33 and of Slco1a1, another amino acids, phosphate, and bicarbonate. Specificexpression transporter, potentially induce alterations in drug pharmacoki- of Hnf4a in the PT seems to play critical roles in the mainte- netics and toxicity. nance of various transporters because Fanconi syndrome, re- Cyp4a10 regulates BP by inhibiting the activity of kidney sulting from a malfunction of the PT, is known to accompany ENaC in the distal tubules.19 Unexpectedly, the present study maturity-onset diabetes of the young type 1 that is caused by revealed DNA demethylation and predominant expression of inactivating mutations in human HNF4a.30 It would be rea- Cyp4a10 in the PT. Because Cyp4a10 has been suggested to sonable to consider that the segmental expression of reab- inhibit ENaC through synthesis of a soluble PPARa ligand, sorption genes in the PT is controlled by DNA methylation Cyp4a10 in the PT may exert its effect on BP in a paracrine of key nuclear receptors such as HNF4a. Many nuclear and manner. In addition, Cyp4a14, another Cyp4a enzyme involved cytoplasmic proteins, including transcription factors and his- in BP regulation, was also significantly demethylated in the PT, tone, are modifiedbytheO-GlcNAcmoiety.31 Mgea5 regulates where its predominant expression has been observed.34 Predom- cellular processes by eliminating the O-GlcNAc modification. inant expression of these Cyp4a enzymes in the PT seems to be The present study revealed relative mRNA enrichment and regulated at the level of DNA methylation. Increased expression DNA demethylation of Mgea5 in the PT, although the difference and further DNA demethylation of Cyp4a10 was observed in the between PT and non-PT fractions was only moderate compared PT of the diabetic kidney. This potentially leads to sodium with that of the other genes described above. The preferential wasting, but the contribution of Cyp4a10 in the PT to BP still distribution of Mgea5 may have some relation to the active needs to be determined.

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Figure 3. Aberrant DNA methylation and induction of Agt mRNA in the PT. (A) DNA methylation status of the Agt promoter analyzed by bisulﬁte sequencing. Top, a diagram of the Agt promoter. The dashes and numbers indicate the positions of the cytosine residues of the CpG dinucleotides relative to the transcription start site (+1). Middle, DNA methylation status of the CpG sites between 2323 and 2629 bp from the transcription start site. Representative results of bisulﬁte sequencing performed with genomic DNA obtained from the PT of 10-week-old control and diabetic mice are shown. The white and black dots represent unmethylated and methylated cytosines, respectively. Bottom, DNA methylation status of the CpG sites between 222 and 2629 bp from the transcription start site (n=4 or 5 mice per group; *P,0.05). At least 20 clones were analyzed in each mouse. (B) Increased Agt mRNA expression in the PT. Results of in situ hybridization of Agt mRNA in the cortex and medulla of db/m (upper panels) and of db/db mice (middle panels) are shown. Asterisks indicate proximal tubules staining positive for Agt mRNA. Hybridization using the sense probe did not yield any detectable signals in the cortex or medulla of db/db mice(lowerpanels).AS,antisenseprobe;S,sense probe. Bar=100 mm.

With all components of the renin-angiotensin system accumulate in the Agt promoter in the diabetic kidney. Among present in the kidney, including Agt in the PT, locally generated these epigenetic changes, H3K9 acetylation is the most sensitive angiotensin II has been suggested to play a significant role in marker of elevated Agt mRNA expression. Because an inhibitor sodium transport, maintenance of BP, and development of of HDAC induced a marked increase of the Agt mRNA level in kidney injury.35 Although basal levels of Agt protein in the HRPTECs, histone acetylation seems to act as a driving mech- kidney are derived from the liver as a result of reabsorption anism. The observation that DNA demethylation and increased by the PT after filtration,36 overexpression of Agt in the PT H3K4 tri-methylation developed in the same time course is induces salt-sensitive hypertension.17 A pathophysiologic role concordant with the previously reported colocalization of hy- for induced Agt expression in the PT and the resultant local pomethylated DNA and increased H3K4 tri-methylation in activation of the renin-angiotensin system has also been sug- cancer cells.39 H3K4 tri-methylation and DNA demethylation gested,37,38 although direct proof must await further studies. could be induced by active transcription, and DNA demethy- We demonstrated that the elevated expression of Agt mRNA in lation may also act as a stabilizing mechanism in mRNA main- the PTwas under the control of epigenetic mechanisms. In the tenance because an inhibitor of DNMTelicited a moderate but PT of the db/db mice, elevation of the Agt mRNA expression significant increase of the Agt mRNA level. preceded demethylation of DNA of the promoter region of In contrast, methylation of Cldn18 markedly increased in Agt. Similarly, H3K9 acetylation of the Agt promoter was in- mice with diabetes. Expression of Cldn18 mRNA was not creased at both weeks 5 and 8 in the diabetic kidney, while observed, even with extended PCR cycles (data not shown), H3K4 tri-methylation was increased only at week 8. These ob- in the PTof control or diabetic mice. The closed chromatin servations indicate that aberrant epigenetic changes gradually status of Cldn18, already present in normal mice, seems to

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Figure 4. Time-dependent epigenetic changes and expression of Agt in the diabetic kidney. (A) DNA methylation of the Agt Figure 5. Epigenetic regulation of AGT mRNA expression in promoter in the PT was determined by COBRA. PT cells were HRPTEC. (A and B) Promoter demethylation and mRNA in- sorted from 5- and 8-week-old db/m and db/db mice (n=6–7per crease of AGT in HRPTECs. HRPTECs were incubated with or group; *P,0.05 versus control mice). (B) Expression of Agt without 100 nM 5-Aza-29-deoxycytidine (5aza) for 96 hours, mRNA in the kidneys of 5- and 8-week-old db/m and db/db and the DNA methylation status of the promoter (A) and mRNA mice (n=6 per group; *P,0.05 versus control mice). (C and D) levels (B) were analyzed (n=4 per group; *P,0.05). (C and D) Histone modifications of the Agt promoter in the kidneys of Promoter acetylation and mRNA increase of AGT in HRPTECs. 5- and 8-week-old db/m and db/db mice (n=6–8 per group; HRPTECs were incubated with or without 300 nM trichostatin A *P,0.05 versus control mice). Histone H3K9 acetylation (C) and (TSA) for 24 hours, and histone H3K9 acetylation of the promoter histone H3K4 tri-methylation (D) status of the Agt promoter were (C) and mRNA levels (D) were analyzed (n=4 per group; determined by chromatin immunoprecipitation assay. n.s., not *P,0.05). D also illustrates the effects of a combination of 5aza significant. and TSA on AGT mRNA expression.GAPDH,glyceraldehyde 3-phosphate dehydrogenase. be further stabilized by the increase in DNA methylation in These observations suggest that epigenetic changes at the the diabetic kidney. Such stabilization has been frequently level of DNA methylation represent and underlie the persis- observed in tumor cells.39 Although its physiologic signifi- tent mRNA changes that potentially lead to phenotypic cance seems to be limited, hypermethylation of genes such changes in the diabetic kidney. However, because we ob- as Cldn18, which show large DNA methylation changes, served refractoriness of the response in only three selected may serve as a good candidate marker for staging of diabetic genes, further analysis is needed to draw the general conclu- kidneys. The finding that both increase and decrease in sion that aberrant DNA methylation defines the phenotypic methylation were observed in diabetic kidneys suggests changes in diabetes. Epigenetic changes could be triggered that changes in DNA methylation may somehow depend by metabolic abnormalities before the start of pioglitazone on the transcription status of each gene, possibly involv- administration and be maintained by some stimuli, such ing multiple chromatin-modifying factors. In the present as albuminuria and blood glucose levels, which pioglitazone study, we focused on the selected genes for analysis of ab- did not prevent completely. Although stricter control of the errant DNA methylation induced by diabetes; therefore, blood glucose levels may attenuate the DNA methylation further genome-wide analysis between control and diabetic changes, the results that pioglitazone did not prevent aber- animals would reveal the other genes with pathophysiologic rant DNA methylation may have some clinical relevance, importance. given that reduction of the blood glucose levels to within the Pioglitazone has been reported to attenuate glomerular normoglycemic range is rarely achieved in many diabetic injury in db/db mice, although the changes in glomerular patients. gene expressions were, in some part, resistant to antidiabetic We used db/db mice with leptin receptor mutation as the therapy.28 These results suggest a wide range of responsiveness model for diabetic kidney disease. Although leptin receptor to diabetic control. In the present study, pioglitazone inhibited mutation is a very rare cause of human type 2 diabetes, the blood glucose elevation, dyslipidemia, albuminuria, renal hy- kidney conditions in the db/db mice mimic many aspects of pertrophy and the decrease of Acaca mRNA expression in the human kidney disease, particularly the changes in the early PT. In contrast, the altered DNA methylation and histone stage.40 Important factors and pathways for the develop- modifications were refractory to pioglitazone treatment. ment of diabetic kidney disease have been clarified using

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In conclusion, the present study revealed genes showing differential DNA methylation within the kidney and indicated the importance of cell-type–specific analysis in organs with multiple components. The finding that ontology and pathway analysis of hypomethylated PT-DMRs illuminated terms of mitochondrial function and biogenesis coincides with the enrichment of mitochondria in the PT and suggests the strict regulation of mitochondrial function, such as metabolism of glucose, lipid, and energy, in the PT by DNA methylation. Indeed, many functionally important molecules in metabolism and transport are under the control of DNA methylation in the PT. Aberrant DNA methylation induced by diabetes was resistant to oral treatment with pioglitazone, a commonly used antidiabetic agent, and underlies persistent mRNA alterations, which likely lead to phenotype changes in the diabetic kidney. Exploration of the mechanisms underly- Figure 6. Persistent DNA methylation alterations resistant to antidiabetic therapy with ing aberrant methylation of the target pioglitazone. (A and B) Blood glucose (A) and kidney weight (B) were determined at the genes revealed in the present study could end of 3 weeks’ administration of pioglitazone to db/db mice (n=9 per group; pave the way to the development of novel *P,0.05). (C) DNA methylation status of the differentially methylated regions with and therapeutic means to prevent and/or re- without pioglitazone treatment. The PT cells were collected from db/m and db/db verse progression of the diabetic kidney ’ mice after 3 weeks administration of pioglitazone or normal chow. DNA methylation disease. of Agt, Abcc4,andSlco1a1 was analyzed by COBRA (n=5 per group; *P,0.05). The CpG sites of the target genes are indicated in Table 1. n.s., not significant. (D) Ex- pression of the target gene mRNA expression with and without pioglitazone treat- CONCISE METHODS ment. Levels of mRNA in the PT cells obtained from db/m and db/db mice after ’ fi 3weeks administration of pioglitazone or normal chow were quanti ed by quantitative Detailed methods are available in the Supple- , RT-PCR (n=5pergroup;*P 0.05). mental Material.

41 Animals this model. WhetheraberrantDNAmethylationincandi- Animal care and treatment complied with the standards described fi date disease-modifying genes, identi ed in the present study, in the Guidelines for the Care and Use of Laboratory Animals of is also induced in human diabetic kidney disease remains to the University of Tokyo. Male C57BLKS/J db/db and db/m mice, 5– be validated in future studies. In this regard, aberrant meth- 10 weeks old, were purchased from Japan CLEA (Tokyo, Japan). ylation of ABCC4 has been reported in the tubular compartment obtained from diabetic patients, while no changes in Sorting of the PT Cells the DNA methylation status in other genes, which were ob- PT cells were stained with Lotus tetragonolobus lectin (Vector served in the present study, such as AGT, were detected in the Laboratories, Burlingame, CA) as the marker and were sorted using study by Ko et al.6 Since the study by Ko et al. included FACSAria III (BD Biosciences, San Jose, CA). patients with CKD without diabetes in the diseased cases, and diabetic patients without renal dysfunction in the controls Cell Culture for the first screening, some genes bearing aberrant DNA meth- HRPTECs (Lonza, Walkersville, MD) were cultured in growth ylation specific for diabetes may not have been detected. Alter- medium (REGM, Lonza) at 37°C in an atmosphere containing natively, purification of the PT, which can eliminate the influ- 5% CO2, and used at passages between 3–5. ence of other cell populations, such as distal tubules, interstitial cells, and vascular compartment, may have led to the identifica- DNA Methylation Analysis tion of the genes specifically altered in the PT in the present DNA methylation profile of PT cells (db/m) was analyzed genome-wide study. by a microarray-based analysis, D-REAM, as described previously.10,42

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Representative DMRs were analyzed by COBRA using a microchip elec- 9. Ziller MJ, Gu H, Müller F, Donaghey J, Tsai LT, Kohlbacher O, De Jager trophoresis system, MutiNA (Shimadzu, Kyoto, Japan) for quantifica- PL, Rosen ED, Bennett DA, Bernstein BE, Gnirke A, Meissner A: tion. Agt promoter was analyzed by bisulfite sequencing. Charting a dynamic DNA methylation landscape of the human genome. Nature 500: 477–481, 2013 10. Yagi S, Hirabayashi K, Sato S, Li W, Takahashi Y, Hirakawa T, Wu G, Analysis of mRNA Levels Hattori N, Hattori N, Ohgane J, Tanaka S, Liu XS, Shiota K: DNA Quantitative RT-PCR analysis was performed with ABI StepOne Plus methylation profile of tissue-dependent and differentially methylated detection system. The signals of in situ hybridization were visualized regions (T-DMRs) in mouse promoter regions demonstrating tissue- using NBT-BCIP solution (Sigma-Aldrich), an alkaline phosphate specific gene expression. Genome Res 18: 1969–1978, 2008 color substrate. 11. Kikuchi R, Yagi S, Kusuhara H, Imai S, Sugiyama Y, Shiota K: Genome- wide analysis of epigenetic signatures for kidney-specific transporters. Kidney Int 78: 569–577, 2010 ChIP Assay 12. Barres R, Kirchner H, Rasmussen M, Yan J, Kantor FR, Krook A, Näslund ChIP assay was performed using antiacetylated histone H3K9 (#9671; E, Zierath JR: Weight loss after gastric bypass surgery in human obesity Cell Signaling Technology, Beverly, MA) or anti–tri-methylated histone remodels promoter methylation. 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Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA: 10-year follow- ACKNOWLEDGMENTS up of intensive glucose control in type 2 diabetes. NEnglJMed359: 1577–1589, 2008 16. Sassi Y, Lipskaia L, Vandecasteele G, Nikolaev VO, Hatem SN, Cohen We thank Mariko Murase for technical assistance. Aubart F, Russel FG, Mougenot N, Vrignaud C, Lechat P, Lompré AM, This work was supported by JSPS KAKENHI (grant numbers Hulot JS: Multidrug resistance-associated protein 4 regulates cAMP- 21229012, 22590879, 24659410, 25461230, and 26670426), Japan dependent signaling pathways and controls human and rat SMC pro- – Foundation for Applied Enzymology, and Daiwa Securities Health liferation. J Clin Invest 118: 2747 2757, 2008 17. Ying J, Stuart D, Hillas E, Gociman BR, Ramkumar N, Lalouel JM, Kohan Foundation. DE: Overexpression of mouse angiotensinogen in renal proximal tubule causes salt-sensitive hypertension in mice. Am J Hypertens 25: 684–689, 2012 REFERENCES 18. 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J Am Soc Nephrol 26: 2388–2397, 2015 DNA Methylation in the Diabetic Kidney 2397 SUPPLEMENTAL MATERIAL

COMPLETE METHODS

Animals

Mice were maintained on a 12-h light/dark cycle and were given access to a standard laboratory diet and water ad libitum. To evaluate the effects of diabetic therapy on the changes in DNA methylation, we administered pioglitazone (Takeda Pharmaceutical,

Osaka, Japan), a peroxisome proliferator–activated receptor-γ agonist, to 5-week-old db/db mice for 3 weeks. Pioglitazone was mixed with normal mouse chow and administered at the dose of 15 mg/kg body wt/day, because 15 mg/kg of pioglitazone has been reported to attenuate albuminuria and changes of glomerular gene expression.1

Mice were killed under anesthesia with pentobarbital. Blood glucose levels were determined with G-checker, a compact glucose analyzer (GUNZE, Tokyo, Japan).

Triglyceride and non-esterified fatty acids were measured using L-type Wako TG-H kit

(Wako Pure Chemical Industries, Tokyo, Japan) and NEFA SS kit (Eiken Co. Ltd.,

Tochigi, Japan), respectively. The urinary albumin concentration was measured using the mouse ELISA kit (Shibayagi, Gunma, Japan).

Cell Culture

To determine the effect of decreased DNA methylation on gene expression, HRPTEC were treated with 100 nM 5-Aza-2’-deoxycytidine for 96 hours and harvested. For evaluation of the effects of HDAC inhibition, HRPTEC were incubated with TSA (300 nM) for 24 hours and harvested. For the combination of DNA demethylation and

HDAC inhibition, cells were incubated with 100 nM 5-Aza-2’-deoxycytidine for 96 hours in combination with 300 nM TSA for the last 24 hours.

Sorting of the PT Cells

The whole kidneys were cut into 5-mm3 pieces with tweezers and scalpel in a Petri dish on ice. The pieces were loaded into a Medicone chamber (CTSV, Turin, Italy), and disaggregated into single cells by microblades spinning at a constant rate of 100 rpm.

Cells were stained with fluorescein isothiocyanate-conjugated Lotus tetragonolobus lectin (Vector Laboratories, Burlingame, CA) as the marker of PT.2, 3 DNA and total

RNA were extracted with AllPrep DNA/RNA Mini (QIAGEN K.K., Tokyo, Japan).

Genome-wide DNA Methylation Analysis

In the D-REAM assay, DNA methylation status at HpyCH4IV sites were indicated by hybridization signals of GeneChip Mouse Promoter 1.0R Array (Affymetrix) with probes mapped to the 8.5-kb regions around transcription start sites of the RefSeq genes in the mouse genome (Build 37.1). Microarray signals were processed by MAT,4 and converted to D-REAM scores of fragments digested in silico by HpyCH4IV. The microarray data of the PT cells isolated in duplicate can be found at Array Express

(www.ebi.ac.uk/arrayexpress/, accession number E-MTAB-2620). By comparing the data of the PT cells (db/m) data with those of the liver, cerebrum, and kidney of

C57BL/6J mice,5, 6 we selected DMRs from HpyCH4IV sites that exhibited significantly different D-REAM scores at cut-off p-value of 10-5. The genes neighboring the DMRs were identified using the Galaxy web server.7, 8 The gene ontology analysis was carried out using the DAVID web server.9

Combined bisulfite restriction analysis (COBRA) and bisulfite sequencing

Bisulfite conversion of 150-500 ng genomic DNA was performed with the EZ DNA

Methylation Kit (Zymo Research, Irvine, CA). The DNA fragments containing the

DMRs were amplified by PCR. PCR was performed using Immolase DNA Polymerase

(Bioline, London, UK) under the following conditions: 95 °C for 7 min; 43 cycles at

94 °C for 1 min, 55 °C or 50°C for 30 s, and 72 °C for 1 min; the final extension step at

72 °C for 10 min. For quantitative-COBRA, the PCR products were digested with

HpyCH4IV, a methylation-sensitive restriction enzyme. After purification by gel filtration with Sephadex G-50 (GE Healthcare Life Sciences, Buckinghamshire, UK), the purified PCR products were analyzed with MutiNA, a microchip electrophoresis system (Shimadzu, Kyoto, Japan) and the methylation levels were quantified. For bisulfite sequencing of the Agt promoter, PCR products were cloned into the pGEM-T

Easy vector (Promega, Madison, WI, USA), and at least 20 clones were chosen randomly from each sample and sequenced. Methylation sites were visualized by the web-based tool, “QUMA” (http://quma.cdb.riken.jp/).

Quantitative RT-PCR analysis

For quantitative RT-PCR analysis, the cDNA product was generated using a high-capacity cDNA archive kit (Applied Biosystems). The expression levels of Agt

(mouse), AGT (human), β-actin, GAPDH, and Abcc4 were then analyzed using the

TaqMan Universal PCR Master Mix (Applied Biosystems). For detection of other genes,

SYBR Green PCR Master Mix (Applied Biosystems) was used. The primers and probes of Agt (mouse), AGT (human), β-actin, GAPDH, Abcc4, and 18S ribosomal RNA were obtained from Applied Biosystems. Expression levels were normalized to those of 18S ribosomal RNA for experiments using the whole kidney and those of β-actin for other experiments with mice. GAPDH was used for normalization in experiments with

HRPTEC.

In Situ Hybridization

Kidneys were fixed with Tissue Fixative (GenoStaff, Inc., Tokyo, Japan), then embedded in paraffin and sectioned at 6 µm. In situ hybridization was performed according to a previously described method.10 For generation of antisense and sense cRNA probes, a 541-bp DNA fragment corresponding to the nucleotide positions 5–545 of the mouse gene for Agt (GenBank accession number NM_007428) was used. Sense probes were used as hybridization control. The bound label was detected using

NBT-BCIP solution (Sigma), an alkaline phosphate color substrate.

ChIP Assay

Frozen kidneys were pulverized by mortar and pestle to a powder before fixation with

10% formaldehyde. ChIP assay was performed in the kidney or HRPTEC as described previously.11 Immunoprecipitated DNA was quantified by quantitative-real time PCR using SYBR Green PCR Master Mix. The enrichment of DNA in the immunoprecipitates was calculated relative to the input samples.

REFERENCES

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FIGURE LEGENDS

Supplemental Figure 1. Characterization of PT-DMRs identified by D-REAM. (A) 6387 PT-DMRs hypomethylated relative to the reference tissues, kidney, liver, and cerebrum, were classified as DMRs unique to a tissue or common to comparisons with at least two tissues.

(B) 5647 PT-DMRs hypermethylated relative to the reference tissues were classified in the same manner as in (A).

Supplemental Figure 2. Validation of the sorted kidney cells obtained from 10 week-old db/db mice.

Expressions of the marker genes of proximal tubules (Sglt2 and Pck1), thick ascending loop of Henle (NKCC2), distal tubules (NCC) and collecting duct (βENaC) in the PT and non-PT fractions (n = 4-5 per group; *p < 0.05). In this and all other supplemental figures, error bars represent mean ± SEM.

Supplemental Figure 3. Aberrant DNA methylation induced by diabetes in the PT cells.

(A) DNA methylation status of the target genes in the PT fraction obtained from 8-10 week-old db/m and db/db mice is shown (n = 5-9 per group; *p < 0.05).

(B) Expression levels of the genes described in (A) are shown. Cldn 18 mRNA was not detected (n = 5 per group; *p < 0.05).

Supplemental Figure 4. Blood glucose levels and body weight of 5- and 8-week old db/m and db/db mice (n = 13 per group; *p < 0.05).

Supplemental Figure 5. Differential effects of pioglitazone on db/db mice.

(A, B) Urinary albumin excretion in 24 hours (A) and the plasma levels of triglyceride and non-esterified fatty acid (NEFA) (B) were determined at the end of 3 weeks’ administration of pioglitazone to db/db mice (n = 6 per group; *p < 0.05).

The mRNA levels in the PT cells obtained from db/m and db/db mice after 3 weeks’ administration of pioglitazone or normal chow were quantified by quantitative RT-PCR

(n=5 per group; *p < 0.05).

(D) DNA methylation status of Cldn18 with and without pioglitazone treatment. PT cells were collected from db/m and db/db mice after 3-weeks’ administration of pioglitazone or normal chow. DNA methylation of Cldn18 was analyzed by COBRA

(n=5 per group; *p < 0.05). The CpG site of Cldn18 is indicated in Table 1. n.s. denotes not significant.

Supplemental Figure 6. Persistent histone modifications resistant to antidiabetic therapy with pioglitazone.

Histone H3K9 acetylation (A) and H3K4 tri-methylation (B) of the promoters of Agt,

Abcc4, and Slco1a1 in the kidneys of db/m and db/db mice after 3-weeks’ administration of pioglitazone or normal chow (n = 4-8 per group; *p < 0.05 vs control mice). n.s. denotes not significant.

Supplemental Table 1. Tissue specificity of transcripts from genes associated with hypo-DMRs in the PT cells.

Comparison Term Count P value Embryo 206 2.02 x 10-10 Mammary tumor 242 1.94 x 10-8 Brain 563 1.71 x 10-7 Kidney Thymus 223 3.51 x 10-7 (1336/1935) Eye 139 1.72 x 10-5 Hippocampus 103 3.64 x 10-5 Kidney 186 6.07 x 10-5 Mammary tumor 226 2.77 x 10-11 Kidney 173 1.05 x 10-6 Liver Embryo 161 8.66 x 10-6 (1148/1643) Bone marrow 118 1.22 x 10-5 Mammary gland 161 4.13 x 10-5 Cerebrum Kidney 247 3.17 x 10-13 (1491/2037) Liver 327 9.66 x 10-8 Kidney 165 6.62 x 10-9 Common Liver 220 7.58 x 10-6 (1057/1455) Spleen 78 7.34 x 10-5

Refseq transcripts harboring PT-DMRs between 6.0 kb upstream and 2.5kb downstream from their TSS were analyzed using the DAVID web server

(http://niaid.abcc.ncifcrf.gov) for their tissue specificity of expression. Significantly

(P-value less than 1.0 x 10-4) enriched terms in the "Uniprot tissue" (UP_TISSUE), which are classified based on literature mining and reports for each gene, are indicated.

PT-DMRs hypomethylated relative to the each reference tissue, namely the kidney, liver, and cerebrum, and common to comparisons with at least two tissues are separately demonstrated. The numbers of DAVID IDs and their corresponding Refseq IDs associated with the PT-DMRs are indicated within parentheses in the left column.

Counts indicate the number of genes involved in the term. Supplemental Table 2. Tissue specificity of transcripts from genes associated with hyper-DMRs in the PT cells.

Comparison Term Count P value Kidney Forelimb 23 2.59 x 10-4 (1565/2128) Liver 326 2.34 x 10-26 Liver Plasma 25 6.58 x 10-11 (1202/1604) Kidney 159 8.63 x 10-5 Brain 582 4.78 x 10-10 Eye 155 7.60 x 10-9 Mammary tumor 240 5.96 x 10-8 Cerebrum Cerebellum 154 3.45 x 10-7 (1342/1921) Hippocampus 111 6.44 x 10-7 Brain cortex 72 1.39 x 10-6 Embryo 187 2.22 x 10-6 Common brain 205 6.15 x 10-4 (482/685)

Tissue specificity of expression from the Refseq genes was analyzed in the same way as that for the analysis shown in Supplemental Table 1. There was no term with a P value of less than 1.0 x 10-4 in the genes associated with PT-DMRs hypermethylated relative to the whole kidney and common to two tissues.

Supplemental Table 3. Functions of genes associated with hypomethylated PT-DMRs.

Enrich -ment Category Term Count P value Score GOTERM_CC_FAT GO:0005739~mitochondrion 111 7.13 x 10-17 SP_PIR_KEYWORDS mitochondrion 71 5.16 x 10-13 GOTERM_CC_FAT GO:0044429~mitochondrial part 53 7.84 x 10-11 GOTERM_CC_FAT GO:0019866~organelle inner membrane 34 5.90 x 10-8 GOTERM_CC_FAT GO:0031966~mitochondrial membrane 37 1.08 x 10-7 7.77 GOTERM_CC_FAT GO:0005743~mitochondrial inner membrane 32 1.89 x 10-7 GOTERM_CC_FAT GO:0005740~mitochondrial envelope 37 4.85 x 10-7 GOTERM_CC_FAT GO:0031967~organelle envelope 44 1.90 x 10-6 GOTERM_CC_FAT GO:0031975~envelope 44 2.18 x 10-6 SP_PIR_KEYWORDS mitochondrion inner membrane 19 7.26 x 10-5 GOTERM_CC_FAT GO:0031090~organelle membrane 53 7.30 x 10-5 SP_PIR_KEYWORDS transit peptide 39 6.65 x 10-7 GOTERM_CC_FAT GO:0005759~mitochondrial matrix 20 9.99 x 10-6 5.28 GOTERM_CC_FAT GO:0031980~mitochondrial lumen 20 9.99 x 10-6 UP_SEQ_FEATURE transit peptide:Mitochondrion 38 1.14 x 10-5 SP_PIR_KEYWORDS ribonucleoprotein 26 6.89 x 10-6 KEGG_PATHWAY mmu03010:Ribosome 15 8.81 x 10-6 SP_PIR_KEYWORDS ribosome 8 8.98 x 10-6 GOTERM_BP_FAT GO:0006412~translation 28 1.08 x 10-5 SP_PIR_KEYWORDS ribosomal protein 20 1.36 x 10-5 4.18 GOTERM_MF_FAT GO:0003735~structural constituent of ribosome 18 1.53 x 10-5 GOTERM_CC_FAT GO:0005840~ribosome 20 9.84 x 10-5 SP_PIR_KEYWORDS protein biosynthesis 16 1.01 x 10-4 GOTERM_CC_FAT GO:0033279~ribosomal subunit 10 7.08 x 10-4 GOTERM_MF_FAT GO:0005198~structural molecule activity 28 0.00318 GOTERM_CC_FAT GO:0030529~ribonucleoprotein complex 30 0.00413 GOTERM_CC_FAT GO:0005903~brush border 12 3.11 x 10-8 GOTERM_CC_FAT GO:0031526~brush border membrane 5 0.00140 2.96 GOTERM_CC_FAT GO:0031253~cell projection membrane 5 0.0746 GOTERM_CC_FAT GO:0044463~cell projection part 8 0.446 The functions of the Kidney genes, that were revealed to be associated with hypomethylated PT-DMRs in Supplemental Table 1, were analyzed using the Functional

Annotation Clustering tool provides by the DAVID web server. The category column indicates the annotation categories involving terms indicated in the term column. The table shows the clusters having terms for which the lowest P values were less than 1.0 x

10-4.

Supplemental Table 4. Functions of genes associated with hypermethylated PT-DMRs.

Enrich -ment Category Term Count P value Score GOTERM_CC_FAT GO:0005739~mitochondrion 28 5.87 x 10-5 SP_PIR_KEYWORDS mitochondrion 19 1.75 x 10-4 GOTERM_CC_FAT GO:0005743~mitochondrial inner membrane 11 4.24 x 10-4 GOTERM_CC_FAT GO:0031966~mitochondrial membrane 12 6.13 x 10-4 GOTERM_CC_FAT GO:0019866~organelle inner membrane 11 6.39 x 10-4 GOTERM_CC_FAT GO:0005740~mitochondrial envelope 12 1.01 x 10-3 2.60 SP_PIR_KEYWORDS transit peptide 12 2.18 x 10-3 GOTERM_CC_FAT GO:0044429~mitochondrial part 13 3.38 x 10-3 GOTERM_CC_FAT GO:0031967~organelle envelope 12 1.15 x 10-2 GOTERM_CC_FAT GO:0031975~envelope 12 1.18 x 10-2 UP_SEQ_FEATURE transit peptide:Mitochondrion 10 2.85 x 10-2 GOTERM_CC_FAT GO:0031090~organelle membrane 14 3.67 x 10-2 SP_PIR_KEYWORDS mitochondrion inner membrane 5 7.53 x 10-2

The functions of genes with PT-DMRs hypermethylated relative to the liver, which were classified into Kidney expression, were analyzed in the same manner as that for the analysis shown in Supplemental Table 3.

Supplemental Table 5. Oligonucleotides used for the bisulfite PCR, and real-time PCR for cDNA and ChIP

Primers used for bisulfite PCR, sequencing Name Position (mm9) F/R Primer sequence (5’ to 3’) F TTGGTGATTTATAGGGGATAGTTTATT Agt promoter A chr8:127093342-127093686 R CAACCTCTATACAAAATAACCCAAAA F AGTTATGTAGATTTTGGGATGAAAGTT Agt promoter B chr8:127093899-127094370 R CCACCCATAATAACCTACAAATAAAAC

Primers used for bisulfite PCR, COBRA (mouse) COBRA Name Position (mm9) Primer name Primer sequence (5’ to 3’) Abcb1b_db_bis_L GTTTTATGTTGTTTGGGTGTTTATT Abcb1b_bis chr5:8799047-8799399 Abcb1b_db_bis_R AATTTACTTTCACTTTATACTTTCC Abcc4_bis3_L AAAGGGAAGAGAGGATATTAAAAGA Abcc4_bis3 chr14:119102417-119102771 Abcc4_bis3_R CAACCAAATAATAACAACCCATACAA Abcc4_db_bis2_L AAGTTTTTTAGGTTTTTATATTTTA Abcc4_bis2 a chr14:119104158-119104491 Abcc4_db_bis2_R TTTCTACCTTTAATAACCATATCCC Acsm2_bis1_L CTATCTCTCTATTTATTCTTTCTCA Acsm2_bis1 chr7:126703699-126704056 Acsm2_bis1_R GTGTGTATTTAGAGGATATATGATT Acsm3_bis_L TAGGGGAGGAATAATAAATAGTGAAT Acsm3_bis chr7:126905846-126906210 Acsm3_bis_R AAAAAATAAACAAAAAAAAACAAAAC Acsm5_bis_L TTAATTTTGTTTTTTTTAGGTTGTGT Acsm5_bis chr7:126669794-126670111 Acsm5_bis_R TTTCTTTAACTCTTCCCTTCTTAAT Acsm5_bis2_L AGGTGAAAAATAGATAGGATTTGGT Acsm5_bis2 chr7:126669569-126669812 Acsm5_bis2_R CTAAAAAAAACAAAATTAAAAATCAAC Agt_bis_F GAATTTTAGAATTGTGATGAAGTTTGT Agt_bis* chr8:127093023-127093304 Agt_bis_R AATAACCAAATCCTTTTACCTCCTATA Apob_bis_1L TTGGAAAATATAAGAAAGTTAAGGT Apob_bis1 chr12:7984976-7985261 Apob_bis_1R ACAATACACAAAAAACAAAAATCC Cdc6_db_bis_L ATAAAAAACACAACTAAATATTAAAA Cdc6_bis chr11:98769822-98770210 Cdc6_db_bis_R TAGTATTAAGGTAGGAAAGGTTGAG Cldn10_bis2_L TTAGTTTTTGTTTTTTGGAGTTGAGG Cldn10_bis2 chr14:119251094-119251362 Cldn10_bis2_R AATTATTTCTTATTCTCTCTCTAAA Cldn18_bis2_L TAAGGAAAATAGTATGAGTAAATAT Cldn18_bis2 chr9:99610320-99610507 Cldn18_bis2_R CAAAAAAAACAAAAAAAACCCTACCAC Cldn18_db_bis_L AGTAGGATAGGATTAAAGATTATGTA Cldn18_bis a chr9:99608935-99609176 Cldn18_db_bis_R AATCAAAAAAAAACCATACAAAACC Cpe_bis_L GAAAATTAGAAGAGAGGTAAAATTA Cpe_bis chr8:67176010-67176379 Cpe_bis_R AACCCAAAAATTATTTTATAAACAC Cpt1a_bis2_L TTCCTCCAACTCTATTTTTATTTT Cpt1a_bis2 chr19:3321141-3321590 Cpt1a_bis2_R ATAGTTTTTTTTTTAAGGATTGTAGTTTT Cpt2_bis2_F GGTTGTGAGTTTAAGGTTTGTTTTAT Cpt2_bis2 chr4:107594088-107594385 Cpt2_bis2_R CCTCAAAATTAAAACTCCTTACCAAAT Cyp4a10_bis_L AAAGGGAATTGGGAAGGGATAGTAT Cyp4a10_bis a chr4:115191836-115192187 Cyp4a10_bis_R CTAAAAACAAAAATAAAACAAACAC Cyp4a14_bis_L AACAAAAATCTCTAAAAAACCAACC Cyp4a14_bis chr4:115169988-115170321 Cyp4a14_bis_R TAGGGAAGGAGAAAGGGTATAAAAT Cyp4b1_bis1_L TTAACAAAAAACCCAACCAAAACC Cyp4b1_bis1 chr4:115319229-115319486 Cyp4b1_bis1_R GGGAGAAATTATATTTTTAAAGTTTG Cdc6_db_bis_L ATAAAAAACACAACTAAATATTAAAA Cdc6_bis chr11:98769822-98770210 Cdc6_db_bis_R TAGTATTAAGGTAGGAAAGGTTGAG Dmdgh_bis_L TAAAAAAAAAGAAAATTGTTAGGG Dmdgh_bis chr13:94444987-94445328 Dmdgh_bis_R TTACAACTCAAAAACTATTCTTAC Enpep_bis_L AATCCTAAAAAAAAAAAACAATACT Enpep_bis chr3:129035201-129035486 Enpep_bis_R TTTAATTGAAAAGGGAAGTTAGTTG Fbp2_bis2_L TAAAATCCCAAAACCTCCCTTTACT Fbp2_bis2 chr13:62959666-62959958 Fbp2_bis2_R AGGATTAAATAAAATAAAATTGGGT Fmo5_bis_L GGTTAGTAAATGGTTTTTTGATTG Fmo5_bis chr3:97428284-97428659 Fmo5_bis_R TTTTATTTTATTCTTCTTTCCCAC G6pc_bis_L GGTTGTTTTTGTGTGTTTGTTTTGTT G6pc_bis chr11:101228839-101229131 G6pc_bis_R AATATTCATTCCTTCCTCCATCCTT G6pc_bis1_L CCTTTACTCTAATTTATTTAACTTT G6pc_bis1 a chr11:101229547-101229762 G6pc_bis1_R ATATAGTTTTATGGGGGAGTTTTTGT Gclm_bis_L TATTTGATTGGTTTGTTAAAAAGT Gclm_bis chr3:121947769-121948149 Gclm_bis_R TTTCCTTTTACTTTACTTTACCCA Gcnt1_bis_L TTGGATTAGGGGATTGAGGAAAATATA Gcnt1_bis a chr19:17447400-17447702 Gcnt1_bis_R TCCCAAAAACCAAAATCTTTCAAA Gcnt1_bis3_L TTTATTTTTTATTATTTTAGGTGAG Gcnt1_bis3 chr19:17434701-17435083 Gcnt1_bis3_R ATCTTCACCACCTTCCAAAAAAACA Gnmt_bis3_F AATTGGGGTAAGTTTGTTTGTTTAG Gnmt_bis3 chr17:46863734-46864220 Gnmt_bis3_R TCCCAAAAACACATAAAAACTCATT Gstz1_bis2_F TTTAAGTTATTGTTGGAATGGAGTTG Gstz1_bis chr12:88489384-88489779 Gstz1_bis2_R AAACACTAACAACAAACCACCTAAC Gys1_bis_L ATTTTTGTGTTTTTGTGAAGGGGTT Gys1_bis chr7:52690664-52691041 Gys1_bis_R CTTTCCCACCTTATATCTAAAAATT Hadh_bis_L AAAAATAAGAAATTATGTGAAAGAAA Hadh_bis chr5:30483161-30483590 Hadh_bis_R AACAAACTCCAAATACAAATCAAAACC Hist2h2aa2_bis_L GTAATTTTATTTTGTTTTTAGTTAAAG Hist2h2aa2_bis chr3:96048010-96048335 Hist2h2aa2_bis_R ATACTCTTCTCTCATCCCTACAAATTA Hnf4a_bis7_F AAAAATCAATCCTATCCAACATAACC Hnf4a_bis7 a chr2:163373462-163373761 Hnf4a_bis7_R TGAAGTTGGGATATAAATTTAAAAAGG Hnf4a_bis8_F TTTGTTTGGTGGTTTTGTATGGTA Hnf4a_bis8 chr2:163373942-163374299 Hnf4a_bis8_R AACCAACTCAAAAACACATATACCC Kif20b_bis_L TTACAAAACCAACACATACAAATAC Kif20b_bis a chr19:34995021-34995357 Kif20b_bis_R AGAAGGAAAAATGAAGAAAGAAATG Ldhb_bis_L AGATTTTTTAATTTTTATAGGGATTT Ldhb_bis chr6:142455910-142456212 Ldhb_bis_R CCCCTACCTATTTCTTCTTTATAATT Lxr_bis1_F TTAGGAAGAGATGTTTTTGTGGTTG Lxr_bis1 chr2:91033432-91033826 Lxr_bis1_R CCACTACCCAACTAATACATCAAAA Met_bis_L TAGTTTTTTGTTTTTGGAATTTTGG Met_bis a chr6:17438380-17438731 Met_bis_R AACTTTCCCTTCTTTTACTAACACTA Met_bis1_L TTAGTTTTTTGTTTTTGGAATTTTGG Met_bis1 chr6:17438379-17438727 Met_bis1_R TTCCCTTCTTTTACTAACACTACTT Met_bis2_L CTTCCATTTCTCTCTTTATTTCTAA Met_bis2 chr6:17441163-17441486 Met_bis2_R GGATATTTTTTGAAGGTTTTTGTTA Met_bis2n_L GGTGATTTGGTTTTATTTGTTATGTG Met_bis2n chr6:17435477-17435701 Met_bis2n_R C ATATAT T T C TA C C T C C AT C C AT T Mgea5_gb_bis_L CTTAAACAAAACAAACAAAAAAACC Mgea5_bis a chr19:45828419-45828766 Mgea5_gb_bis_R GGATTGAAAATGAAATAGAATTGAG Nudt19_bis_L AGGAAGGAGTTAAGTTTTGATTTAA Nudt19_bis chr7:36342624-36342990 Nudt19_bis_R AAAATATAATTATAACCCTCTAACAC Pck1_bis_L AGTTTAATTATTATTTTTTTGGAGT Pck1_bis chr2:172978395-172978680 Pck1_bis_R CTACCTACCTTTCTTCCTTTTAAAAA Pck1_bisn_L AAATAAATAAAACCAAACCCCAAACC Pck1_bisn chr2:172979616-172979782 Pck1_bisn_L TAGGATTTGTAGAGAATATTTTAAT Pck1_bisn1_L ACATCAACAACAAACAAAATCAAAA Pck1_bisn1 a chr2:172978288-172978547 Pck1_bisn1_R AAATATTATATAGAAGGGAGGATAG Pdk3_bis2_L AATTAGAAAAAAAAAAGGTAAAAG Pdk3_bis2 chrX:91078798-91079165 Pdk3_bis2_R CACCCAAAAAAATAAATAAACAACC Pdp1_bis_L AC C C C AT C C AT T C T T TATA ATATAC T Pdp1_bis chr4:11892199-11892514 Pdp1_bis_R GTTTTTTTTTATTTTTGTAGATATTG Proc_bis1_F ATTGTAAGATTGTGAAGGATTGTGG Proc_bis1 chr18:32297365-32297769 Proc_bis1_R CTAATATCCCCCAAACCAAATAAAC Serpina1e_bis1_F TTTTTGGGAGTAGGGGTAATATAGG Serpina1e_bis1 chr12:105194600-105194996 Serpina1e_bis1_R ACACAAATCTCCCAAACCACTATAC Slc2a5_bis1_L ATTATTTCTATACCCCACCTCTCA Slc2a5_bis1 a chr4:149493621-149493821 Slc2a5_bis1_R GTTTTTTTTTAGGAAAATTTTTTTG Slc2a5_bis2_L AAGGGTGAAGGATAAGAAGAAAGA Slc2a5_bis2 chr4:149493893-149494137 Slc2a5_bis2_R CAAAACAAACTAAATCCCCAAAAA Slc5a2_bis1_L AGGAATATGTATGTTTTGTTGATTGTT Slc5a2_bis1 a chr7:135408837-135409185 Slc5a2_bis1_R AACTAATCCCTAAATTCCCCTAAAA Slc5a2_bis_L CAAACCCTAAACTAAAACATTTAC Slc5a2_bis chr7:135411459-135411821 Slc5a2_bis_R GATATTTAAGAAGGTTAGAAGTTT Slco1a_F TGTGTGTGTATGGATTTGTTTGTTT Slco1a_F a chr6:141895647-141896048 Slco1a_R AACCACTCTTCCCAAATTACTCTAA Socs2_db_bis_L TTTTCCTCTTAAATAATTCTATACAC Socs2_bis chr10:94880798-94881161 Socs2_db_bis_R ATTTTTGTATATTGTAGAGGTTTAA Suclg2_bis_L AATTTATTTTTTTTCCCACCAAACC Suclg2_bis chr6:95666262-95666607 Suclg2_bis_R GGGTGAATGTTTTTTTTTTTTGTTAATAG a Primers used in Table 1, Figures 1, 2 and 4, and Supplemental Figures 3 and 5D.

Primers used for bisulfite PCR, COBRA (human) COBRA Name Position (GRCh37/hg19) Primer name Primer sequence (5’ to 3’) AGT_bis_L CCAGTGTAGCTGGGGAGACTGTTAAAC AGT_bis chr1:230850702-230850705 AGT_bis_R CACTGAAGGGACAGGAAGGAAGATCCT

Primers used for real-time PCR for cDNA Name Accession Number F/R Sequence (5’ to 3’) F CTGGAGGACCCAACAACAAC Acaca NM_133360 R GAGCAGTTCTGGGAGTTTCG F TCCCATCACCTCCTTTTCAC Cyp4a10 NM_010011 R TGCACGACACAATTTCCTGT F CTCGGGGAGCAATATACGAG Cyp4a14 NM_007822 R CATTCAACAGGAGCAAACCA F TCGGAACTTCACGCCTATCT βENaC NM_011325 R CCGATGTCCAGGATCAACTT F CGAGGAAAGAAAAAGCCAAC G6pc NM_008061 R CCAGAATCCCAACCACAAGA F CTGGAACCCAATGAAACCTT Gcnt1 NM_010265 R CAACAGCCATGCTAAATGGA F AGAGGTTCTGTCCCAGCAGA Hnf4a NM_008261 R ATGTACTTGGCCCACTCGAC F TTTCCTTAGTCGCCTCAAAC Kif20b NM_183046 R ATCCAAAACTTGCACACAGC F AGCATTTTTACGGACCCAAC Met NM_008591 R ACAGCCGGAAGAGTTTCTCA F TACCAAGCCAAATGGTGACA Mgea5 NM_023799 R ACACCTCCTGCTCTTCATGG F CCTCCATCACCAACTCACCT NCC NM_001205311 R CCGCCCACTTGCTGTAGTAT F TGTGAAGTTTGGATGGGTGA NKCC2 NM_183354 R CAGGAGAGGCGAATGAAGAG F AGGAGTACGGGCAGTTGCT Pck1 NM_011044 R TCTGCTCTTGGGTGATGATG F CTGAACTTGGGGAGCAGAAG Sglt2 NM_133254 R GGCAGCGATAACCAGAATGT F TACAACGTAGCTGCCGTCAA Slc2a5 NM_019741 R CAGCGTCAAGGTGAAGGACT F TTAAAGCCAACGCAAGATCC Slco1a1 NM_013797 R GGGAGTTTCACCAATTCCAC

Primers used for real-time PCR for ChIP (mouse) Name Position (mm9) F/R Sequence (5’ to 3’) F TACTCAAGGGGTGGAGATGG Agt chr8:127093635-127093725 R AGCCTGGATTCTCATGGTTC F GTGTAAGGCTGTGCAGGAAA Abcc4 chr14:119105134-119105270 R GCGTGTTCTTCTGGTGAGTG F CAACAGAAGGCCACTCTTCC Slco1a1 chr6:141895639-141895725 R TGAACCACCACCTCCCTATC

Primers used for real-time PCR for ChIP (human) Name Position (GRCh37/hg19) F/R Sequence (5’ to 3’) F AACAGGGCATGACAGAGACC AGT chr1:230850646-230850747 R TAAGGCTGGACACATCACCA

Kidney Liver 1443 1552 1360

Cerebrum 6387 2032

Kidney Liver

2004 1442 578

Cerebrum 1623 5647

Supplemental Figure 1

0.5 mRNA ( fold change) 0 * * sglt2 pck1

50 * *

25 mRNA ( fold change) 0 NKCC2 NCC βENaC

Supplemental Figure 2 A

) 80 % ( db/m db/db * 60 * * * 40 *

methylation * 20 * *

DNA 0 Abcc4 Agt Cyp4a10 Met Slc2a5 Cldn18 Kif20b Slco1a1

B 5 * db/m db/db (fold) * 2.5 * *

mRNA * * * 0 Abcc4 Agt Cyp4a10 Met Slc2a5 Kif20b Slco1a1

Supplemental Figure 3 db/m db/db

800 40

400 20 (mg/dl) Blood glucose Body weight (g) 0 0 5w 8w 5w 8w

Supplemental Figure 4

A 300 g/d ) µ

db/m (

db/db 150

db/db piog

Albuminuria 0 B

dL )

300 ) 700 /L (mg/

Eq µ ( 150 350 EFA N 0 0 Triglyceride

C D 80 n.s.

mRNA 40 0.5 Acaca

0 methylation DNA (%) 0 Cldn18

Supplemental Figure 5 db/m db/db db/db piog A H3K9Ac n.s. n.s. n.s. 1.5 2 1 1 1 0.5 0.5

Fold of control 0 Fold of control 0 Fold of control 0 Agt Abcc4 Slco1a1

B H3K4me3

n.s. 2 n.s. n.s.

1.5 1 1 1 0.5 0.5

Fold of control 0 Fold of control 0 Fold of control 0 Agt Abcc4 Slco1a1 Supplemental Figure 6