RAGE deletion confers renoprotection by reducing responsiveness to Transforming Growth Factor-β and increasing resistance to apoptosis

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1 RAGE deletion confers renoprotection by reducing responsiveness to Transforming Growth Factor-β and increasing resistance to apoptosis Journal: Manuscript ID DB R1 Manuscript Type: Original Article: Complications Date Submitted by the Author: 28-Dec-2017 Complete List of Authors: Hagiwara, Shinji; Juntendo University, Internal Medicine; Baker IDI Heart and Institute Sourris, Karly; Monash University, ; Baker IDI Heart and Institute Zeimann, Mark; Monash University, ; Baker IDI Heart and Institute Wu, Tieqiao; Monash University, ; Baker IDI Heart and Institute Mohan, Muthukumar; Monash University, ; Baker IDI Heart and Institute McClelland, Aaron; Baker IDI Heart and Institute Brennan, Eoin; University College Dublin, Conway Institute; Baker IDI Heart and Institute Forbes, Josephine; Mater Research Institute - UQ, Translational Research Insitute; University of Queensland, School of Medicine Coughlan, Melinda; Monash University, ; Baker IDI Heart and Institute Harcourt, Brooke; Murdoch Childrens Research Institute, Hormone Research Penfold, Sally; Monash University, ; Baker IDI Heart and Institute Wang, Bo; Monash University, Biomedicine Discovery Insitute; Baker IDI Heart and Institute Higgins, Gavin; Monash University, ; Baker IDI Heart and Institute Pickering, Raelene; Monash University, ; Baker IDI Heart and Institute El-Osta, Assam; Monash University, ; Baker IDI Heart and Institute Thomas, Merlin; Monash University, ; Baker IDI Heart and Institute Cooper, Mark; Monash University, ; Baker IDI Heart and Institute Kantharidis, Phillip; Monash University, Department of ; Baker IDI Heart and Institute Publish Ahead of Print, published online February 15, 2018

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3 Page 2 of 38 Title: RAGE deletion confers renoprotection by reducing responsiveness to Transforming Growth Factor-β and increasing resistance to apoptosis Authors and Affiliations: Shinji Hagiwara 1,2, Karly Sourris 1,2, Mark Ziemann 1,2, Wu Tieqiao 1,2, Muthukumar Mohan 1,2 Aaron D McClelland 2, Eoin Brennan 1.2, Josephine Forbes 3, Melinda Coughlan 1,2, Brooke Harcourt 4, Sally Penfold 1,2, Bo Wang 2,5, Gavin Higgins 1,2, Raelene Pickering 1,2, Assam El- Osta 1,2, Merlin C Thomas 1,2, Mark E Cooper 1,2, Phillip Kantharidis 1,2. 1 Department of, Monash University, Melbourne, Australia. 2 JDRF Danielle Alberti Memorial Centre for Complications, Division, Baker IDI Heart and Institute, Melbourne, Australia. 3 Mater Clinical School, University of Queensland, St Lucia, Brisbane, Australia. 4 Centre for Hormone Research, Murdoch Children s Research Institute, Melbourne, Australia. 5 Kidney Regeneration and Stem Cell Laboratory, Monash University, Australia. Contact information: Correspondence: Dr. Phillip Kantharidis, Department of, Monash University, Alfred Campus, 99 Commercial Road, Melbourne 3004, Australia. Ph: , Key Words: AGE, RAGE, diabetic nephropathy, renal physiology, TGF-β, apoptosis, S100A4. Running title: RAGE deletion confers renoprotection 1

4 Page 3 of 38 Abstract Signalling via the receptor of advanced glycation end-products (RAGE) although complex and not fully elucidated in the setting of diabetes, is considered a key injurious pathway in the development of diabetic nephropathy (DN). We report here that RAGE deletion resulted in increased expression of fibrotic (collagen I and IV, fibronectin) and the inflammatory marker, MCP-1 in primary mouse mesangial cells (MC) and in kidney cortex. RNA-seq analysis in MCs from RAGE -/- and wild type mice confirmed these observations. Nevertheless, despite these gene expression changes a decreased responsiveness to transforming growth factor-β was identified in RAGE -/- mice. Furthermore, RAGE deletion conferred a more proliferative phenotype in MCs and reduced susceptibility to staurosporine-induced apoptosis. RAGE restoration experiments in RAGE -/- MCs largely reversed these gene expression changes resulting in reduced expression of fibrotic and inflammatory markers. This study highlights that protection against DN in RAGE KO mice is likely in part to be due the result of decreased responsiveness to growth factor stimulation and an anti-apoptotic phenotype in mesangial cells. Furthermore, it extends our understanding of the role of RAGE in the progression of DN since RAGE appears to play a key role in modulating the sensitivity of the kidney to injurious stimuli such as prosclerotic cytokines. 2

5 Page 4 of 38 Introduction RAGE is a cell surface multiligand receptor 1, 2 and a member of the immunoglobulin superfamily playing a role in tissue repair early in disease 3 but also linked to chronic proinflammatory gene activation in the pathogenesis of several diseases including Alzheimer s disease, rheumatoid arthritis, cancer and diabetic complications 4. In the kidney, AGE binding to RAGE results in the increased expression of growth factors and cytokines such as TGF-β, connective tissue growth factor (CTGF), vascular endothelial growth factor (VEGF) and MCP-1, ultimately leading to glomerular and tubulointerstitial injury 5. Transgenic overexpression of RAGE worsens kidney disease in both non-diabetic and diabetic mice 6 whereas administration of soluble RAGE 7 or RAGE-neutralizing antibodies 8 confers protection against complications, similar to that observed in RAGE -/- mice 7, Specific targeting of RAGE as a therapeutic treatment remains controversial since RAGE plays a key role in both innate and adaptive immune responses 4, 13, 14, lung homeostasis, bone metabolism, the immune system and nervous system 15. A better understanding of the role of RAGE in physiological processes and particularly in the kidney is required since RAGEdirected therapeutic strategies are being considered for diabetic nephropathy (DN). The present study reveals an important homeostatic role for RAGE in the normal kidney and specifically in MCs. RAGE deletion resulted in increased macrophage infiltration in the diabetic kidney despite improved renal function and decreased mesangial expansion. Gene profiling experiments demonstrated that RAGE -/- MCs were less responsive to the actions of TGF-β, resulting in the down-regulation of several signalling pathways, despite an increase in the baseline expression of fibrotic and inflammatory markers. Restoring RAGE expression in the RAGE -/- MCs by adenoviral delivery returned the expression of fibrotic, inflammatory and cell survival genes to control levels. These observations contribute to our understanding 3

6 Page 5 of 38 of the renoprotection conferred by RAGE deletion in response to diabetes. Methods Cell culture MCs were isolated from the kidneys from C57BL6/J 16 and RAGE -/- mice on a C57BL6/J background 17 by collecting glomeruli after sieving (106, 180, and 75 µm pore size respectively), and culturing MC outgrowths in DMEM (20%FCS) as previously described for rats. 9, 18. MCs were identified as positive for desmin, Thy-1.1 and αsma expression, negative for von Willebrand factor, and by morphological evaluation 19. MCs were cultured up to 10 passages in DMEM (20% FCS). For experiments, cells were seeded at /well in 6-well plates. Fresh DMEM (2% FCS) was added after 24hrs, +/- TGF-β1 (R&D systems) in normal (5.5 mm) or high (25 mm) glucose (HG), and cells were incubated a further 3 days. Unless otherwise specified, in vitro studies were conducted in HG medium. Cell proliferation, viability and apoptosis For proliferation, MCs were seeded at /well and the medium replaced with DMEM (5% FCS) after 24hrs. Cells were counted with the Tali Image-Based Cytometer (Life Technologies). For viability, cells were seeded at /well and the next day cells were starved in DMEM (no FCS) for 24hrs. Cell death was assessed using the Tali TM Viability kit, (1:100, Life Technologies). For apoptosis, cells were seeded at /well on collagen I coated cover slips. The next day cells were treated with staurosporine (12.5nM, Sigma- Aldrich) for 24hrs to induce apoptosis before immunostaining for active caspase 3 (1:500; Neuromics). 4

7 Page 6 of 38 Western blotting Primary antibodies were collagen I (1:5000; Abcam), αsma (1:2000; Dako), phospho-smad3 (1:1000; Invitrogen), smad3 (1:5000; Origene), phospho-erk (1:500; Cell Signaling), ERK (1:1000; Cell Signaling), S100A4 (1:1000; Cell signaling), P53 (1:500; Abcam) and β-actin (1:10000; Abcam). Secondary antibodies were goat anti-mouse (1:20000; Dako) or goat antirabbit HRP conjugated (1:10000; Dako). Adenovirus-Mediated RAGE Gene Transfer In vitro Human Full-length (FL) and ES-RAGE cdna (gift of Prof. H. Yamamoto 20 ) were subcloned into AdEasy-1 (Ad-FL-RAGE and Ad-ES-RAGE) 9. The padtrack-cmv without RAGE was used as an empty vector control. Virus was packed using HEK293 cells. MCs were seeded at /well and grown to 60% confluence in DMEM (10% FCS). The medium was then replaced with DMEM (2% FCS) containing Ad-FL-RAGE, Ad-ES-RAGE vector or empty vector (2.85x10 8 optical particle units). After 3 days cells were harvested for gene expression analysis. Transfection efficiency was 80 to 90% on the basis of GFP fluorescence. Transfection of sirna Cells were seeded at cells/well in 12-well plates in DMEM (10% FCS) without antibiotics. Medium was replaced with DMEM (2% FCS) and cells were transfected with sirna at 5nM for RAGE or 10nM for S100A4 using RNAiMAX (Invitrogen) with sirna negative controls used at the same concentration. Cells were harvested 24 hrs post transfection. RAGE sirna was transfected on two consecutive days and cells were harvested 48 hrs after the first transfection. RNA extraction and real-time PCR 5

8 Page 7 of 38 Total RNA (2µg) extracted from the left kidney cortex or MCs was used to synthesize cdna as previously described 21. Gene expression was analyzed by real-time (rt-) PCR using the TaqMan system (ABI Prism 7500; Perkin-Elmer) and normalized to 18S rrna (18S rrna TaqMan Control Reagent kit, Perkin-Elmer). Results were expressed relative to control (untreated) cells, which were arbitrarily assigned a value of 1, with 4-6 replicates per group. RNA-seq library preparation and sequencing RNA was quantified using Qubit fluorometer and integrity was assayed using Multi-NA bioanalyzer (Shimadzu, Japan). NEBNext Poly(A) mrna Magnetic Isolation Module was used to enrich mrna from 1 µg of total RNA. Following elution of mrna, we used the NEBNext Ultra Directional RNA Library Prep Kit from Illumina to generate barcoded libraries. Libraries were validated by Multi-NA bioanalyzer (Shimadzu), pooled to equimolar ratios and sequenced at the Australian Genome Research Facility (Melbourne) using Illumina HiSeq2500 with version 4 single end flow cell and reagents for 60 cycles. Bioinformatics analysis Single end mrna-seq reads underwent quality trimming to remove low quality bases from the 3 end of reads using FASTXToolkit (version ) using a Phred quality threshold of 20 and minimum 20nt read length. STAR version was used to align reads to the mouse genome (Mus_musculus.GRCm38.dna.toplevel.fa) downloaded from Ensembl ( using the default settings. We used Ensembl version 77 gene annotations (Mus_musculus.GRCm38.77.gtf). Exon mapped reads were counted using featurecounts version with a mapping quality threshold of 10. Genes with fewer than 10 reads per sample on average were excluded from downstream analysis. Multidimensional scaling analysis was performed using the cmdscale function in R. Statistical analysis of 6

9 Page 8 of 38 differential gene expression was conducted using edger software version 0.20 with the default settings 24. Factorial edger was performed to identify genes and pathways whose differential regulation in response to TGF-β treatment is dependent upon the presence of RAGE. To facilitate pathway analysis, mouse gene identifiers were mapped to human gene names using a mouse human homolog relationship table downloaded from Ensembl BioMart ( Pathway analysis was performed using GSEA-P software version using the unweighted classic scoring scheme 50. Gene sets for pathway analysis were downloaded from MSigDB ( Heatmaps were generated in base R. In vivo experiments Male mice were injected with streptozotocin (55 mg/kg IP daily, 5 consecutive days, diabetic) 25 or sodium citrate buffer (control). After 10 days, plasma glucose levels were determined (Accutrend; Boehringer Mannheim Biochemica, Mannheim, Germany) and mice overtly diabetic (>15 mm; >95% of mice). The diets (AIN-93G; Specialty Feeds, Glen Forrest, Perth, Australia) and water were provided ad libitum. Mice were housed in specific pathogen-free conditions with exposure to 12:12-h light-dark cycles for 24 weeks (n=8/group). All animal studies were performed in accordance with the guidelines of the AMREP Animal Ethics Committee and the NHMRC of Australia. At the end of the study, kidneys and plasma were collected for analysis, and glycated hemoglobin (GHb) was determined by HPLC 26. Albumin excretion rate (AER) was determined by ELISA (Bethyl Laboratories, Montgomery, TX) 27, and creatinine in urine and plasma was determined by HPLC (Agilent HP1100 system; Hewlett Packard, Böblingen, Germany) as recommended 28. Glomerular sclerotic index (GSI) was assessed using a semiquantitative method and pointcounting technique 29. Tubulointerstitial area (TIA) was assessed using a point-counting 7

10 Page 9 of 38 technique 30. Immunohistochemistry Sections (4µm) were stained for collagen IV (1:600, rabbit polyclonal; Abcam). Briefly, sections were dewaxed, hydrated, and quenched with 3% H 2 O 2 in Tris-buffered saline (TBS) and digested with 0.4% pepsin (Sigma-Aldrich) in 0.01 M HCl at 37 C. Sections were blocked with 0.5% milk/tbs and incubated with the primary antibody for 24hrs/4 C. After avidin/biotin blocking, biotinylated anti-rabbit IgG (1:500) was applied as the secondary antibody for 10mins/RT. For CD68 and CD169 immunostaining, frozen sections (5µM) were air-dried and fixed in 2% paraformaldehyde-lysine-periodate (PLP)/10min. Sections were stained for CD68+ (1:500; BD Biosciences) leucocytes overnight/4 C as well as for CD169 (1:200; Serotec) 90min/RT. After washing, sections were incubated in 0.6% H 2 O 2 /TBS for 20min/RT, followed by avidin/biotin blocking. Sections were incubated with biotinylated rabbit anti-rat IgG, 1:200) for 1hr/RT. Finally, horseradish peroxidase conjugated streptavidin (VECTASTAIN Elite ABC Staining Kit; Vector Laboratories) was added and sections incubated for 30min/RT. Peroxidase conjugates were visualized using 3,3 -diaminobenzidine tetrahydrochloride (Sigma-Aldrich) in 0.08% H 2 O 2 /TBS. Sections were finally counterstained with Mayer s hematoxylin, dehydrated, and mounted. Sections were examined under a light microscope (Olympus BX-50; Olympus Optical, Tokyo, Japan) and digitized with a high-resolution camera. Collagen IV positive staining in the cortex (20 cross-sections per animal, magnification x200) was quantitated using Image- Pro plus 6 (Media Cybernetics) 31. CD68+ and CD169+ leukocytes were counted in the glomerulus (15 hilar glomerular tuft cross-sections (GCS) per animal, magnification x400). 8

11 Page 10 of 38 All assessments were performed in a blinded manner. Five or six kidneys were investigated in each group. MCP-1, TGFβ1 and Fibronectin ELISA 50 mg of renal cortex was homogenised (Polytron PT-MR2100) in extraction buffer to isolate cytosol and membranous fractions as previously described 32. Total protein was determined by the BCA method (Pierce). MCP-1 levels in renal cortical cytosolic fractions were determined by sandwich ELISA (R&D Systems). Renal cytosolic fractions were concentrated using Microcon filters (Ultra Cel YM membrane, 10K, Millipore Corporation). TGFβ1 ELISA was run on acid treated cortical cytosolic fractions to measure total TGFβ1 protein levels (TGFβ1 Emax ImmunoAssay kit, Promega Corporation). Fibronectin was measured by ELISA in renal cortical fractions by ELISA (Mouse Fibronectin PicoKine ELISA Kit, Boster Biological Technology). Mesangial Expansion, glomerulosclerosis and tubulointerstitial fibrosis Kidney sections were stained with Periodic Acid Schiff s (PAS) stain for quantitation of glomerulosclerosis. The degree of glomerulosclerosis which was defined as thickening of the glomerular basement membrane and mesangial expansion, was evaluated by a semiquantitative method as described previously 29, 31. Tubulointerstitial collagen deposition was assessed in twenty fields (X40) following Masson s Trichrome staining using Image-Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD) as previously described. 11 Tubulointerstitial area was evaluated in PAS-stained sections by point counting, as previously described 29. Mesangial area was analyzed (percentage of glomerular area) from digital pictures of glomeruli (15 20 glomeruli per kidney per animal) using Image-Pro Plus, as described previously. 11 9

12 Page 11 of 38 Statistical Analysis Statistical analyses were performed using GraphPad Prism 6.0 (GraphPad Software, San Diego, CA). Values of experimental groups are shown as mean, with bars showing the SEM, unless otherwise stated. One-way ANOVA with Tukey post test analysis or two-way ANOVA with Bonferroni post test analysis were used to determine statistical significance. Where appropriate a two-tailed t-test was performed. P<0.05 was considered statistically significant. Differential gene expression by mrna-seq was determined by edger 24 and differential pathway regulation was determined with GSEA-P 33. The Benjamini-Hochberg method was used for false discovery rate (FDR) correction of EdgeR and GSEA-P results 34. FDR adjusted p values 0.05 were considered significant. Results Deletion of RAGE is renoprotective in STZ-diabetic mice Gene expression, extracellular matrix (ECM) protein levels and macrophage infiltration were examined in the cortex of kidneys from non-diabetic and STZ-diabetic WT and RAGE -/- mice at 24 weeks of diabetes. Plasma glucose and glycated Hb (GHb) were similarly elevated in both WT and RAGE -/- diabetic mice (Figure 1A and 1B). Urinary albumin excretion rate (AER) (Figure 1C), creatinine clearance (CrCl) (Figure 1D), glomerular damage and glomerulosclerotic index (GSI) (Figure 1E) were all elevated in diabetic WT mice but were significantly reduced in the diabetic RAGE -/- mice. The tubulointerstitial area (TIA) was elevated in the kidneys of diabetic WT and RAGE -/- mice (Figure 1E). Although renal Collagen IV staining was further increased in the cortex of diabetic RAGE -/- mice, glomerular Collagen IV levels were in fact reduced compared to diabetic WT mice (Figure 1F). 10

13 Page 12 of 38 Furthermore, glomerular expansion which was increased in diabetic wild type mice, was absent in the kidneys of diabetic RAGE -/- mice (Fig 1G). Similarly, genetic deletion of RAGE prevented the increased expression of Fibronectin and TGFβ1 protein induced by diabetes in the kidneys of wild type diabetic mice (Fig 1H and I). The observed reno-protective effect of RAGE deletion was observed despite the elevated renal expression of COL1A1, αsma, MCP-1 (CCL2), TGFBR1, C5AR1, COL4A3, fibronectin (FN1) and Ki67 (MKI67) in the diabetic WT and diabetic RAGE -/- mice (Figure 2A-H). Renal MCP-1 protein levels were also further elevated in diabetic RAGE -/- kidney (Figure 2I). The macrophage markers, CD68 and CD169 were elevated in RAGE -/- mouse kidney and further increased in diabetic RAGE -/- mice (Figure 2J and K), however the glomerular CD169+:CD68+ ratio, a measure of macrophage activation was similar in both WT and RAGE -/- diabetic mice (Figure 2L). RAGE deletion results in down-regulation of TGF-β inducible signalling pathways Since renal function, GSI, mesangial expansion and Col IV expression were improved in the glomeruli of RAGE -/- mice despite the overall increased levels of fibrotic and inflammatory markers, we decided to further study the renoprotective effect of RAGE deletion focusing on the glomerulus, specifically in MCs. RNA-seq experiments were performed on primary mouse WT and RAGE -/- MCs grown in the presence or absence of TGF-β. Multidimensional Scaling (MDS) analysis demonstrated distinct and reproducible differences among the four sample groups (Figure 3A). A Smear plot demonstrated significantly altered expression of 7842 genes (red points) following TGF-β treatment of WT MCs (Figure 3B). Only 5223 genes (red points) were significantly altered in by TGF-β in RAGE -/- MCs (Figure 3C). A factorial analysis investigating the effect of RAGE deletion on TGF-β mediated gene regulation demonstrated that 5246 genes were RAGE dependent (Figure 3D). In this analysis, 11

14 Page 13 of 38 red dots in the positive region show a greater fold induction in RAGE -/- MCs with TGF-β whilst those in the negative region demonstrate a reduced fold change in RAGE -/- MCs in response to TGF-β. This is more clearly demonstrated in the scatter plot of fold changes for TGF-β treatment in WT cells versus RAGE -/- MCs (Figure 3E). There are relatively few genes that show discordant fold changes. The Gene Set Enrichment Analysis (GSEA) analysis of the Reactome gene pathways are shown in Figure 3F. Pathways such as metabolism of proteins, cholesterol biosynthesis, adaptive immune system, extracellular matrix organization, class I MHC mediated antigen presentation, collagen formation, axon guidance, apoptosis, metabolism of carbohydrates and translation are significantly down-regulated in RAGE -/- MCs. On the other hand, only the generic transcription pathway is significantly up-regulated in RAGE -/- MCs. For example, cholesterol biosynthesis and collagen formation gene sets exhibit striking downregulation (Figure 3G). Down-regulation of these pathways is consistent with their induction by TGF-β being diminished in RAGE -/- MCs. A heatmap of cholesterol biosynthesis genes shows TGFβ exposure causes up-regulation of these genes in WT MCs whereas these genes are downregulated in RAGE -/- MCs (Figure 3H). Similarly, collagen synthesis genes are downregulated in RAGE -/- MCs; with COL8A2 one of the most significant differential expression events (Figure 3I, FDR p=2.64e-39). RAGE deletion promotes pro-fibrotic, pro-survival and pro-inflammatory gene expression RT-PCR analysis of gene expression revealed upregulation of several fibrotic and inflammatory genes, transcription factors and cell survival genes in RAGE -/- MCs under baseline conditions. COL4A1, COL4A3, PKCα and β, and DIAPH1 (which is known to interact with RAGE 35 ) were significantly down-regulated (Table 1). The RAGE ligand, S100A4 was up-regulated 22-fold in RAGE -/- MCs. 12

15 Page 14 of 38 High glucose (HG) had no effect on baseline gene expression in WT MCs, however baseline expression of COL1A1 and MCP-1 was significantly elevated in RAGE-/- MCs under HG conditions (Table 2). TGF-β increased the expression of COL1A1, αsma, PAI-1, Fibronectin and COL4A3 in WT MCs (Table 2). By contrast, the fold-change in expression of these genes in response to TGF-β was attenuated in RAGE -/- MCs. αsma protein was increased in RAGE -/- MCs (Figure 4a) compared to WT MCs. While TGF-β further increased αsma in WT MCs, it did not alter αsma levels in RAGE -/- MCs. MCP1 protein was also elevated in control RAGE -/- MCs but significantly reduced by TGFβ (Fig 4b), a similar pattern to that seen with respect to MCP1 RNA levels (Table 2). Fibronectin protein levels are induced by TGFβ in both WT and RAGE -/- MCs, but the effect was attenuated in the RAGE -/- MCs, a similar pattern to that seen with respect to fibronectin RNA levels (Table 2). Collectively, these data demonstrate that RAGE -/- MCs were less responsive to TGF-β compared to WT MCs, confirming the observations in the RNA-seq data (see Figure 3). Deletion of RAGE promotes proliferation in MCs and protects against apoptosis Cell growth rate was significantly increased in RAGE -/- MCs compared to WT MCs (Figure 5A). Propidium iodide staining demonstrated fewer dead (positive staining) RAGE -/- MCs over time compared to WT MCs following FCS depletion (Figure 5B). Staining for active caspase 3 following staurosporine treatment revealed fewer apoptotic nuclei in RAGE -/- MCs compared to WT MCs (Figure 5C-D). From these data, RAGE -/- MCs appeared to have acquired a more proliferative and an anti-apoptotic phenotype. Elevated TGF-β and ERK signaling in MCs from RAGE -/- mice Smad3 and ERK phosphorylation were both significantly increased in RAGE -/- compared to WT MCs indicating increased activity of TGF-β and ERK pathways respectively (Figure 6A- 13

16 Page 15 of 38 B). S100A4, a ligand known to signal through RAGE and toll like receptors (TLR) was significantly up-regulated in RAGE -/- cells (Figure 6C). The level of p53 was also significantly reduced in RAGE -/- MCs (Figure 6D), consistent with the anti-apoptotic phenotype of these cells. Knockdown of S100A4 by sirna increased p53 protein levels (Figure 6E) and decreased expression of αsma, MCP-1, TGFBR1, COL4A3, PAI-1 and Ki67 in RAGE -/- MCs (Figure 6F). These data support the view that RAGE deletion promotes the expression of cell survival genes and the baseline increase of profibrotic and inflammatory pathways. RAGE modulates inflammatory, fibrotic and apoptotic processes Based on the above data, we hypothesized that RAGE may play a role in inflammatory, fibrotic and cell survival processes under normal physiological conditions. RAGE knockdown by sirna in WT MCs increased the expression of profibrotic and inflammatory genes (COL1A1, αsma, MCP-1 and TGFBR1; Supplementary Figure 1. Interestingly, restoring the expression of (full length) FL-RAGE in RAGE -/- MCs decreased expression of COL1A1, αsma, MCP-1, TGFBR1, PAI-1 and S100A4 to levels observed in WT MCs (Table 3). These data clearly demonstrate an anti-inflammatory and anti-fibrotic role for FL- RAGE in MCs. Interestingly, endogenous secretory (ES-) RAGE, a novel splice variant of RAGE was equally as effective as FL-RAGE in restoring the expression of most genes in RAGE -/- MCs (Table 3). We further explored this effect and observed HMGB1 increased the expression of COL1A1, αsma, NFκB-P65, TGFBR1, PAI-1 and COL4A3 in RAGE -/- MCs (Supplementary Figure 2). However, when this experiment was repeated with ES-RAGE adenovirus infected RAGE -/- MCs, HMGB1 had little effect on the expression of these genes. In contrast, overexpression of FL-RAGE in WT MCs increased the expression of COL1A1, 14

17 Page 16 of 38 αsma, MCP-1, TGFBR1, PAI-1, fibronectin, COL4A3 and S100A4 (Table 3). Interestingly, ES-RAGE decreased the expression of MCP-1, PAI-1 and S100A4 (Table 3) in these cells. Taken together, these data reveal a complex role for FL-RAGE in kidney where RAGE negatively regulates inflammatory and fibrotic processes under normal physiological conditions, but also promotes these pathological processes when RAGE expression is increased. Discussion In this study, we examined the effect of genetic deletion of RAGE on diabetic kidney gene expression, structure and function. We observed the resolution of hyperfiltration, an early renal functional change seen in both human and experimental diabetes, reduced albuminuria and less glomerular structural injury in diabetic RAGE -/- mice compared to diabetic WT mice. This was despite the increased expression of a range of well characterised fibrotic and inflammatory markers in the kidney cortex of diabetic RAGE -/- mice. Furthermore, increased macrophage infiltration was also observed in diabetic RAGE -/- mouse kidneys, but importantly this was not accompanied with increased renal injury. Interestingly, a previous study has demonstrated the requirement for RAGE expression to mediate the HMGB1 activation of MAPK and SAPK/JNK pathways in macrophages, but not for the reduction of TNF-α, IL-1β and IL-6 levels 36. It was also demonstrated that diabetic WT mice reconstituted with RAGE -/- bone marrow had improved renal function and reduced renal injury compared to diabetic WT mice reconstituted with WT bone marrow 37. These studies, along with our data, confirm that RAGE expression on haemopoietically derived immune cells contributes to the pathological changes seen in DN. 15

18 Page 17 of 38 RNA-seq analysis of MCs derived from both WT and RAGE -/- mice revealed gene expression differences involving several signalling pathways relevant to DN. In particular, the effect of TGF-β on gene expression was attenuated in RAGE -/- MCs. Interestingly, RAGE is known to co-operate with TGF-β 5, 38, the angiotensin II type 1 receptor subtype and TLR signalling 41 pathways resulting in the amplification of fibrotic and inflammatory responses Our data are consistent with these studies which demonstrate that renoprotection in RAGE - /- MCs is in part due to the reduced responsiveness to growth factor stimulation of these injurious pathways in DN. Despite the reduced responsiveness to TGF-β, increased expression of pro-fibrotic and inflammatory genes was observed in RAGE -/- MCs compared to WT MCs. Compensatory signaling via TGF-β, TLR receptors and immune system pathways may account for this since elevated S100A4, TGFBR1, TLR4 and C3aR1 were observed (Table 1), as well as activated SMAD3 and ERK which are downstream mediators of these pathways (Figure 6). Activation of TLR signaling is mediated by many ligands including S100A4, a member of the family of S100 calcium binding proteins, which acts through TLR4 to activate MyD88, the transcription factor that drives NF-kB and the tyrosine kinases ERK1/2 and p38 expression in mononuclear cells 42. This proinflammatory pattern observed in the kidneys of RAGE -/- mice in our study has also been observed in the peritoneum by Liliensiek et al. although in a different disease context. 17 The pro-survival phenotype observed in RAGE -/- MCs may also contribute to renoprotection in diabetic RAGE -/- mice. Loss of glomerular cells occurs through apoptosis in experimental DN 43 and apoptosis of MCs correlates with worsening of albuminuria 44. Patients with mild diabetic renal injury display a six-fold increase in apoptotic glomerular cells which is associated with a loss in kidney function

19 Page 18 of 38 RAGE restoration experiments in RAGE -/- MCs suggest a protective role for RAGE in the normal kidney against fibrotic and inflammatory processes. Delivery of FL-RAGE or ES- RAGE reversed the up-regulation of pro-fibrotic and inflammatory genes (Table 3). The reverse experiment with knockdown of RAGE in WT MCs complemented these observations, resulting in increased expression of fibrotic and inflammatory genes (Supplementary Figure 1). These data support a homeostatic role for RAGE in normal kidney cells. RAGE plays a protective role under normal physiological conditions where it regulates the inflammatory response to a variety of different ligands, including AGEs. However sustained activation of RAGE results in inflammation and promotes the micro and macrovascular complications of diabetes Our RNA seq data indicate that RAGE enhances the TGFβ mediated activation signalling pathways including pathways related to the metabolism of proteins, cholesterol biosynthesis, adaptive immune systems, ECM organization and collagen formation (Fig 3). Consistent with our findings, Englert et al. demonstrated that RAGE -/- mice develop more severe lung fibrosis than WT controls in a model of pulmonary fibrosis 49. RAGE overexpression highlighted the complex role of RAGE in normal physiology. FL- RAGE delivery in WT MCs increased the expression of profibrotic and inflammatory genes, whereas ES-RAGE decreased the expression of some of these genes (Table 3). Our data results are consistent with previous reports of a pathological role for FL-RAGE when overexpressed 6 and the beneficial effect of ES-RAGE 7, the decoy receptor, in the diabetic context. RAGE -/- MCs were resistant to apoptosis induced by staurosporine, via activation of caspase- 3 50, and serum starvation (Figure 5), potentially via up-regulation of S100A4. Overexpression of S100A4 is observed in cancer and directly interacts and results in the degradation of nuclear p Consistent with these reports, decreased p53 protein levels were observed in 17

20 Page 19 of 38 RAGE -/- MCs (Figure 6D) and knock down of S100A4 resulted in increased p53 (Figure 6E). The importance of S100A4 in fibrosis has been previously been reported in other tissues 52. Our findings suggest that up-regulation of S100A4 contributes to the pro-survival and profibrotic phenotype of RAGE -/- MCs. RAGE plays a major role in the development and progression of DN and is highly expressed in response to various RAGE ligands which are elevated in the diabetic context 54. Our findings identify a key physiological role for RAGE in the kidney by regulating the expression of pro-fibrotic and inflammatory genes as well as influencing cell survival under normal conditions. The direct targeting FL-RAGE may therefore not be an ideal therapeutic approach but rather strategies that target the AGE/RAGE interaction either by directly inhibiting ligands such as HMGB1 and AGEs, or using the decoy receptor such as srage may be preferable. Acknowledgements SH was supported by the Manpei Suzuki Foundation. This study was also supported by the Australia Research Trust. PK was supported by the Vera Dalgleish Phillips Fellowship and the NHMRC. MEC is supported by the NHMRC. This study was also supported in part by the Victorian Government s Operational Infrastructure Support Program. K.S, M.Z, BW, ADM, WT, MM, MC, BH, SP, GH, RP, AO, MCT and PK researched data. JF, MEC, and PK reviewed/edited manuscript. SH researched data and wrote manuscript. PK is the guarantor. No conflict of interest for SH, KS, MZ, ADM, EB, WT, MM, JF, MC, BH, SP, BW, GH, RP, AO, MCT, JF, MEC and PK. 18

21 Page 20 of 38 References 1. Bierhaus A, Humpert PM, Morcos M, Wendt T, Chavakis T, Arnold B, et al. Understanding RAGE, the receptor for advanced glycation end products. Journal of molecular medicine 2005;83(11): Xie J, Mendez JD, Mendez-Valenzuela V, Aguilar-Hernandez MM. Cellular signalling of the receptor for advanced glycation end products (RAGE). Cell Signal 2013;25(11): Clynes R, Moser B, Yan SF, Ramasamy R, Herold K, Schmidt AM. Receptor for AGE (RAGE): weaving tangled webs within the inflammatory response. Curr Mol Med 2007;7(8): Moser B, Desai DD, Downie MP, Chen Y, Yan SF, Herold K, et al. Receptor for advanced glycation end products expression on T cells contributes to antigen-specific cellular expansion in vivo. Journal of immunology 2007;179(12): Li JH, Huang XR, Zhu HJ, Oldfield M, Cooper M, Truong LD, et al. Advanced glycation end products activate Smad signaling via TGF-beta-dependent and independent mechanisms: implications for diabetic renal and vascular disease. FASEB journal : official publication of the Federation of American Societies for Experimental Biology 2004;18(1): Yamamoto Y, Kato I, Doi T, Yonekura H, Ohashi S, Takeuchi M, et al. Development and prevention of advanced diabetic nephropathy in RAGE-overexpressing mice. The Journal of clinical investigation 2001;108(2): Wendt TM, Tanji N, Guo J, Kislinger TR, Qu W, Lu Y, et al. RAGE drives the development of glomerulosclerosis and implicates podocyte activation in the pathogenesis of diabetic nephropathy. The American journal of pathology 2003;162(4): Flyvbjerg A, Denner L, Schrijvers BF, Tilton RG, Mogensen TH, Paludan SR, et al. Long-term renal effects of a neutralizing RAGE antibody in obese type 2 diabetic mice. 2004;53(1): Coughlan MT, Thorburn DR, Penfold SA, Laskowski A, Harcourt BE, Sourris KC, et al. RAGE-induced cytosolic ROS promote mitochondrial superoxide generation in diabetes. Journal of the American Society of Nephrology : JASN 2009;20(4): Myint KM, Yamamoto Y, Doi T, Kato I, Harashima A, Yonekura H, et al. RAGE control of diabetic nephropathy in a mouse model: effects of RAGE gene disruption and administration of low-molecular weight heparin. 2006;55(9): Soro-Paavonen A, Watson AM, Li J, Paavonen K, Koitka A, Calkin AC, et al. Receptor for advanced glycation end products (RAGE) deficiency attenuates the development of atherosclerosis in diabetes. 2008;57(9): Tan AL, Sourris KC, Harcourt BE, Thallas-Bonke V, Penfold S, Andrikopoulos S, et al. Disparate effects on renal and oxidative parameters following RAGE deletion, AGE accumulation inhibition, or dietary AGE control in experimental diabetic nephropathy. American journal of physiology Renal physiology 2010;298(3):F Manfredi AA, Capobianco A, Esposito A, De Cobelli F, Canu T, Monno A, et al. Maturing dendritic cells depend on RAGE for in vivo homing to lymph nodes. Journal of immunology 2008;180(4): Tian J, Avalos AM, Mao SY, Chen B, Senthil K, Wu H, et al. Toll-like receptor 9- dependent activation by DNA-containing immune complexes is mediated by HMGB1 and RAGE. Nature immunology 2007;8(5):

22 Page 21 of Ott C, Jacobs K, Haucke E, Navarrete Santos A, Grune T, Simm A. Role of advanced glycation end products in cellular signaling. Redox biology 2014;2: Freeman HC, Hugill A, Dear NT, Ashcroft FM, Cox RD. Deletion of nicotinamide nucleotide transhydrogenase: a new quantitive trait locus accounting for glucose intolerance in C57BL/6J mice. 2006;55(7): Liliensiek B, Weigand MA, Bierhaus A, Nicklas W, Kasper M, Hofer S, et al. Receptor for advanced glycation end products (RAGE) regulates sepsis but not the adaptive immune response. The Journal of clinical investigation 2004;113(11): Schulze-Lohoff E, Hugo C, Rost S, Arnold S, Gruber A, Brune B, et al. Extracellular ATP causes apoptosis and necrosis of cultured mesangial cells via P2Z/P2X7 receptors. Am J Physiol 1998;275(6 Pt 2):F Hagiwara S, Makita Y, Gu L, Tanimoto M, Zhang M, Nakamura S, et al. Eicosapentaenoic acid ameliorates diabetic nephropathy of type 2 diabetic KKAy/Ta mice: involvement of MCP-1 suppression and decreased ERK1/2 and p38 phosphorylation. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 2006;21(3): Yonekura H, Yamamoto Y, Sakurai S, Petrova RG, Abedin MJ, Li H, et al. Novel splice variants of the receptor for advanced glycation end-products expressed in human vascular endothelial cells and pericytes, and their putative roles in diabetesinduced vascular injury. The Biochemical journal 2003;370(Pt 3): Kantharidis P, Hagiwara S, Brennan E, McClelland AD. Study of microrna in diabetic nephropathy: isolation, quantification and biological function. Nephrology 2015;20(3): Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013;29(1): Liao Y, Smyth GK, Shi W. featurecounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 2014;30(7): Robinson MD, McCarthy DJ, Smyth GK. edger: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010;26(1): Forbes JM, Yee LT, Thallas V, Lassila M, Candido R, Jandeleit-Dahm KA, et al. Advanced glycation end product interventions reduce diabetes-accelerated atherosclerosis. 2004;53(7): Cefalu WT, Wang ZQ, Bell-Farrow A, Kiger FD, Izlar C. Glycohemoglobin measured by automated affinity HPLC correlates with both short-term and long-term antecedent glycemia. Clinical chemistry 1994;40(7 Pt 1): Coughlan MT, Thallas-Bonke V, Pete J, Long DM, Gasser A, Tong DC, et al. Combination therapy with the advanced glycation end product cross-link breaker, alagebrium, and angiotensin converting enzyme inhibitors in diabetes: synergy or redundancy? Endocrinology 2007;148(2): Dunn SR, Qi Z, Bottinger EP, Breyer MD, Sharma K. Utility of endogenous creatinine clearance as a measure of renal function in mice. Kidney international 2004;65(5): Forbes JM, Thallas V, Thomas MC, Founds HW, Burns WC, Jerums G, et al. The breakdown of preexisting advanced glycation end products is associated with reduced renal fibrosis in experimental diabetes. FASEB journal : official publication of the Federation of American Societies for Experimental Biology 2003;17(12):

23 Page 22 of Hewitson TD, Darby IA, Bisucci T, Jones CL, Becker GJ. Evolution of tubulointerstitial fibrosis in experimental renal infection and scarring. Journal of the American Society of Nephrology : JASN 1998;9(4): Watson AM, Gray SP, Jiaze L, Soro-Paavonen A, Wong B, Cooper ME, et al. Alagebrium reduces glomerular fibrogenesis and inflammation beyond preventing RAGE activation in diabetic apolipoprotein E knockout mice. 2012;61(8): Thallas-Bonke V, Thorpe SR, Coughlan MT, Fukami K, Yap FY, Sourris KC, et al. Inhibition of NADPH oxidase prevents advanced glycation end product-mediated damage in diabetic nephropathy through a protein kinase C-alpha-dependent pathway. 2008;57(2): Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genomewide expression profiles. Proceedings of the National Academy of Sciences of the United States of America 2005;102(43): Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological) 1995;57(No. 1 ): Rai V, Maldonado AY, Burz DS, Reverdatto S, Yan SF, Schmidt AM, et al. Signal transduction in receptor for advanced glycation end products (RAGE): solution structure of C-terminal rage (ctrage) and its binding to mdia1. The Journal of biological chemistry 2012;287(7): Kokkola R, Andersson A, Mullins G, Ostberg T, Treutiger CJ, Arnold B, et al. RAGE is the major receptor for the proinflammatory activity of HMGB1 in rodent macrophages. Scandinavian journal of immunology 2005;61(1): Tesch G, Sourris KC, Summers SA, McCarthy D, Ward MS, Borg DJ, et al. Deletion of bone-marrow-derived receptor for AGEs (RAGE) improves renal function in an experimental mouse model of diabetes. Diabetologia 2014;57(9): Fukami K, Ueda S, Yamagishi S, Kato S, Inagaki Y, Takeuchi M, et al. AGEs activate mesangial TGF-beta-Smad signaling via an angiotensin II type I receptor interaction. Kidney international 2004;66(6): Matsui T, Yamagishi S, Takeuchi M, Ueda S, Fukami K, Okuda S. Irbesartan inhibits advanced glycation end product (AGE)-induced proximal tubular cell injury in vitro by suppressing receptor for AGEs (RAGE) expression. Pharmacological research : the official journal of the Italian Pharmacological Society 2010;61(1): Nakamura K, Yamagishi S, Nakamura Y, Takenaka K, Matsui T, Jinnouchi Y, et al. Telmisartan inhibits expression of a receptor for advanced glycation end products (RAGE) in angiotensin-ii-exposed endothelial cells and decreases serum levels of soluble RAGE in patients with essential hypertension. Microvascular research 2005;70(3): Ibrahim ZA, Armour CL, Phipps S, Sukkar MB. RAGE and TLRs: relatives, friends or neighbours? Molecular immunology 2013;56(4): Cerezo LA, Remakova M, Tomcik M, Gay S, Neidhart M, Lukanidin E, et al. The metastasis-associated protein S100A4 promotes the inflammatory response of mononuclear cells via the TLR4 signalling pathway in rheumatoid arthritis. Rheumatology 2014;53(8): Pesce C, Menini S, Pricci F, Favre A, Leto G, DiMario U, et al. Glomerular cell replication and cell loss through apoptosis in experimental diabetes mellitus. Nephron 2002;90(4):

24 Page 23 of Mishra R, Emancipator SN, Kern T, Simonson MS. High glucose evokes an intrinsic proapoptotic signaling pathway in mesangial cells. Kidney international 2005;67(1): Verzola D, Gandolfo MT, Ferrario F, Rastaldi MP, Villaggio B, Gianiorio F, et al. Apoptosis in the kidneys of patients with type II diabetic nephropathy. Kidney international 2007;72(10): Chawla D, Bansal S, Banerjee BD, Madhu SV, Kalra OP, Tripathi AK. Role of advanced glycation end product (AGE)-induced receptor (RAGE) expression in diabetic vascular complications. Microvascular research 2014;95: Tobon-Velasco JC, Cuevas E, Torres-Ramos MA. Receptor for AGEs (RAGE) as mediator of NF-kB pathway activation in neuroinflammation and oxidative stress. CNS Neurol Disord Drug Targets 2014;13(9): Yan SF, Ramasamy R, Schmidt AM. The receptor for advanced glycation endproducts (RAGE) and cardiovascular disease. Expert Rev Mol Med 2009;11:e Englert JM, Hanford LE, Kaminski N, Tobolewski JM, Tan RJ, Fattman CL, et al. A role for the receptor for advanced glycation end products in idiopathic pulmonary fibrosis. The American journal of pathology 2008;172(3): Chae HJ, Kang JS, Byun JO, Han KS, Kim DU, Oh SM, et al. Molecular mechanism of staurosporine-induced apoptosis in osteoblasts. Pharmacological research : the official journal of the Italian Pharmacological Society 2000;42(4): Ebralidze A, Tulchinsky E, Grigorian M, Afanasyeva A, Senin V, Revazova E, et al. Isolation and characterization of a gene specifically expressed in different metastatic cells and whose deduced gene product has a high degree of homology to a Ca2+binding protein family. Genes & development 1989;3(7): Mishra SK, Siddique HR, Saleem M. S100A4 calcium-binding protein is key player in tumor progression and metastasis: preclinical and clinical evidence. Cancer metastasis reviews 2012;31(1-2): Orre LM, Panizza E, Kaminskyy VO, Vernet E, Graslund T, Zhivotovsky B, et al. S100A4 interacts with p53 in the nucleus and promotes p53 degradation. Oncogene 2013;32(49): Tanji N, Markowitz GS, Fu C, Kislinger T, Taguchi A, Pischetsrieder M, et al. Expression of advanced glycation end products and their cellular receptor RAGE in diabetic nephropathy and nondiabetic renal disease. Journal of the American Society of Nephrology : JASN 2000;11(9):

25 Page 24 of 38 Table 1. Baseline expression of selected profibrotic, pro-inflammatory and cell survival genes assessed by RT-PCR in RAGE -/- compared to WT MCs Gene Fold increase p value S100A E-12 CCL2 (MCP-1) E-11 SNAI SERPINE1 (PAI-1) ACTA2 (αsma) COL1A C3AR VEGFA SNAI BCL TGFBR MKi TIMP TWIST ZEB SMAD VIM MMP COL3A TLR PRKCB DIAPH PRKCA COL4A COL4A

26 Page 25 of 38 Table 2. Expression of selected pro-fibrotic and pro-inflammatory genes assessed by RT-PCR in RAGE -/- and wild type MCs in low or high glucose, with or without TGFβ1 treatment. Gene WT MCs RAGE KO MCs Low Glucose High Glucose Low Glucose High Glucose Control TGFβ1 Control TGFβ1 Control TGFβ1 Control TGFβ1 Col Iα1 1 ± ± ± ± ± ± ± ± 0.94 αsma 1 ± ± ± ± ± ± ± ± 0.48 MCP-1 1 ± ± ± ± ± ± ± ± 0.75 S100A4 1 ± ± ± ± ± ± 3 26 ± ± 2.6 TGFBR1 1 ± ± ± ± ± ± ± ± 0.24 PAI-1 1 ± ± ± ± ± ± ± ± 1.8 Fibronectin 1 ± ± ± ± ± ± ± ± 0.43 Col IVa3 1.1 ± ± ± ± ± ± ± ± 0.43 p<0.05 versus control for each group (n=6-10/group). Data shown is the mean ± standard error. All comparisons are relative to the low glucose WT control for each gene. Wild Type (WT), knock out (KO), mesangial cells (MC). 24

27 Page 26 of 38 Table 3. Expression of certain pro-fibrotic and pro-inflammatory genes assessed by RT-PCR in RAGE -/- and WT MCs with adenoviral delivery of full length (FL) or, endogenous secretory RAGE (ES-R) Gene EV FL-R ES-R Col I 1 ± ± ± 0.09 αsma 1 ± ± ± 0.1 MCP-1 1 ± ± ± 0.11 RAGE -/- TGFBR1 1 ± ± ± 0.16 MCs PAI-1 1 ± ± ± 0.25 Col IVα3 1 ± ± ± 0.2 Fibronectin 1 ± ± ± 0.29 S100A4 1 ± ± ± 0.1 Col I 1 ± ± ± 0.11 αsma 1 ± ± ± 0.11 MCP-1 1 ± ± ± 0.11 TGFBR1 1 ± ± ± 0.19 WT MCs PAI-1 1 ± ± ± 0.11 Col IVα3 1 ± ± ± 0.19 Fibronectin 1 ± ± ± S100A4 1 ± ± ± 0.12 P<0.05 relative to EV control. Wild Type (WT), knock out (KO), mesangial cells (MC), empty vector (EV), FL-R or ES-R. Data shown is the mean ± standard error. 25

28 Page 27 of 38 Figure legends Figure 1. Metabolic and renal functional parameters. Plasma glucose was measured using a glucometer (A). Glycated hemoglobin was determined by high-performance liquid chromatography (HPLC) (B). Urinary albumin excretion rate (AER) was determined by ELISA (C). Creatinine clearance (CrCl) was determined by HPLC (D). Wild type (WT), wild type diabetic mice (WT D), receptor for AGE (RAGE)-deficient mice (R(-)), diabetic RAGE-deficient mice (R(-) D). (E) Representative image of PASstained renal tissue, Tubulointerstitial Area (TIA) and Glomerulosclerotic index (GSI). PASperiodic acid Schiff staining of kidney cortex in WT, WT D, R(-) and R(-) D. GSI was determined at week 24. For RT-PCR analysis, total RNA was extracted from kidney cortex of wild type (WT), wild type diabetic mice (WT D), RAGE-deficient mice (R(-)) and diabetic RAGE-deficient mice (R(-) D). Magnification of x400 (scale bar=50µm). (F) Immunostaining of COLIV is significantly up-regulated in non-diabetic R(-) kidney compared to non-diabetic WT kidney at 24 weeks of age. Furthermore, collagen IV expression was most significantly up-regulated in R(-) D kidney among all the groups, but the induction was less in the glomeruli in R(-) D mice compared to WT D mice. Magnification of x200 (scale bar=50µμ). Mesangial expansion was quantified (G), and fibronectin (H) and TGFβ1 (I) proteins levels were quantified by ELISA. (P < 0.05 vs. WT. P < 0.05 vs. R(-). P < 0.05 vs. WT D. Values are means ± SD; n=6 8 per group.) Figure 2. Expression of fibrotic and inflammatory markers. The gene expression of COL1α1 (A), αsma (B), MCP-1 (C), TGFBR1 (D) C5AR1 (E), COL4α3 (F), fibronectin (G) and Ki67 (H) were significantly up-regulated in R(-) or R(-) D 26

29 Page 28 of 38 kidney cortex compared to WT. Renal cortical MCP-1 protein levels were up-regulated in diabetic WT mice and were further upregulated in diabetic RAGE -/- mice (I). Glomerular CD68+ macrophages were increased in non-diabetic RAGE -/- mice and further increased in diabetic RAGE -/- mice (J). CD 169+ macrophages were increased in diabetic WT mice and further increased in diabetic RAGE -/- mice (K). The calculated glomerular CD169+:CD68+ macrophage ratio was increased with diabetic WT mice and diabetic RAGE -/- mice at the similar level (L). P < 0.05 vs. WT. P < 0.05 vs. R(-). P < 0.05 vs. WT D. Values are means ± SD, n=6 8 per group. Figure 3. RNA-seq analysis of the effect of TGF-β on RAGE -/- mouse mesangial cells. (A) MDS plot of TGF-β treated (10ng/ml) and control mouse MC gene expression. (B) Smear plot of gene expression changes in TGF-β treated and control WT MCs. Genes with FDR p-values 0.05 are highlighted in red. (C) Smear plot of gene expression change in TGF-β treated and control RAGE -/- MCs. (D) MA plot showing the effect of RAGE -/- on the TGF-β mediated regulation. Smear plot of factorial analysis shows 5246 genes, whose TGF-β regulation is dependent upon RAGE (FDR p-values 0.05). (E) Scatter plot of fold changes for TGF-β treatment in WT cells versus KO cells. X-axis shows changes in wild type cells and y-axis shows RAGE -/- cells. Genes with FDR p-values > 0.05 are not shown. (F) GSEA analysis of Reactome gene pathways. The normalised enrichment score (NES) indicates the direction of pathway regulation. Gene sets with an asterisk are significant (FDR p-values 0.05). (G) Enrichment plot of cholesterol and collagen gene sets on a 1 dimensional line of genes ranked from most up-regulated (red) to most down-regulated (blue). (H) Heatmap of cholesterol biosynthesis genes (red; low expression, yellow; high expression). (I) Heatmap of collagen formation genes. 27

30 Page 29 of 38 Figure 4. Gene and Protein expression in WT and RAGE -/- MCs treated with TGF-β. WT and RAGE -/- MCs were cultured in the presence of TGF-β1 (10 ng/ml, 3 days) in high glucose conditions. Protein expression of αsma (A) was quantified by Western blotting. MCP-1 (B) and fibronectin (C) protein levels were determined by ELISA. Data are expressed as mean ± SD ( P < 0.05 vs WT cont, P < 0.05 TGF-β treated RAGE KO MCs vs TGF-β treated WT MCs). Figure 5. Cell proliferation, viability and apoptosis in WT and RAGE -/- MCs. WT cells and R(-) cells were cultured in DMEM containing 5% FCS. Cell numbers were counted on day 1, 3 and 7 (A). WT and R(-) MCs were cultured in DMEM without FCS and the total cell number and PI positive dead cells were counted on day 1, 3 and 7 (B). (C) WT and R(-) MCs were cultured in DMEM containing 2% FCS and treated with 12.5 nm of staurosporine to induce apoptosis. Immunostaining of active caspase 3 was performed and cells with fragmented nuclei and active caspase 3 were counted (white arrows). R(-) MCs are GFP positive. Images were captured using x60 objective with x12.5 digital zoom (scale bar is 20µM). Apoptotic cells are significantly lower in R(-) cells than WT cells (D). P < 0.05 Figure 6. RAGE deletion affects the expression of phospho-smad3, phospho-erk, s100a4 and p53. Western blot analysis of phospho-smad3 (A), phospho-erk (Β), S100A4 (C) and p53 levels (D) in R(-) MCs compared to WT under low and high glucose conditions. R(-) MCs were transfected with s100a4 sirna (10 nm) resulting in significantly decreased S100A4 and 28

31 Page 30 of 38 increased p53 protein levels (E). Knock down of S100A4 in R(-) MCs decreased the RNA levels of αsma, MCP-1, TGFBR1, COL4A3, PAI-1 and Ki67 (F). P < 0.05 vs WT or sirna Control. 29

32 Page 31 of 38 Figure 1 A B C D E Non diabetic Diabetic WT R(-) F Non diabetic Diabetic WT R(-) G H I M esangial expansion (% A r e a ) W T W T D R (-) R (-) D F ib r o n e c tin (n g /m g p ro te in ) W T W T D R (-) R (-) D T G F 1 a c tiv ity (p g /m g p ro te in ) W T W T D R (-) R (-) D

33 Figure 2 Page 32 of 38 A B C D E F G H I J K L

34 Page 33 Figure of 38 3A-E A B C D E

35 Figure 3F-I Page 34 of 38 F G H I

36 Page 35 of 38 Figure 4 A WT MCs RAGE KO MCs TGF α-tubulin SMA αsma protein Fold Increase C o n t T G F - C o n t T G F - WT MCs RAGE KO MCs B MCP-1 (μg/mg protein) C o n t T G F - C o n t T G F - WT MCs RAGE KO MCs C Fibronectin (μg/mg protein) C o n t T G F - C o n t T G F - WT MCs RAGE KO MCs

37 Figure 5 Page 36 of 38 A B C GFP DAPI(Blue) Active caspase 3 (Red) D WT MC RAGE(-) MC Apoptotic cells/total cells(%) WT RAGE(-)

38 Page 37 of 38 Figure 6 A p-smad3 smad3 WT RAGE (-) B WT RAGE (-) p-erk ERK p-ssmad3/smad3 Fold increase C WT RAGE (-) D WT RAGE (-) S100A4 β-actin p53 β-actin E RAGE (-) S100A4 sirna S100A4 GAPDH p53 β-actin F Fold increase 1.6 SiRNA Control SiRNA S100A4 RAGE (-)

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