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Lipoxins Regulate the Early Growth Response–1 Network and Reverse Diabetic Disease

Eoin P. Brennan,1,2 Muthukumar Mohan,1,3 Aaron McClelland,1 Christos Tikellis,1,3 Mark Ziemann,1,4 Antony Kaspi,1,4 Stephen P. Gray,1 Raelene Pickering,1,3 Sih Min Tan,1,3 Syed Tasadaque Ali-Shah,5 Patrick J. Guiry,5 Assam El-Osta,1,4 Karin Jandeleit-Dahm,1,3 Mark E. Cooper,1,3 Catherine Godson,2 and Phillip Kantharidis1,3

1Juvenile Diabetes Research Foundation Danielle Alberti Memorial Centre for Diabetes Complications, Diabetes Division, Baker IDI and Diabetes Institute, Melbourne, Victoria, Australia; 2University College Dublin Diabetes Complications Research Centre, UCD Conway Institute of Biomolecular and Biomedical Research, UCD School of Medicine and Medical Sciences, and 5Centre for Synthesis and Chemical Biology, UCD School of Chemistry and Chemical Biology, University College Dublin, Dublin, Ireland; and 3Department of Diabetes and 4Epigenetics in Health and Disease Laboratory, Department of Diabetes, Central Clinical School, Monash University, Clayton, Victoria, Australia

ABSTRACT Background The failure of spontaneous resolution underlies chronic inflammatory conditions, including microvascular complications of diabetes such as diabetic kidney disease. The identification of endoge- nously generated molecules that promote the physiologic resolution of inflammation suggests that these bioactions may have therapeutic potential in the context of chronic inflammation. Lipoxins (LXs) are lipid mediators that promote the resolution of inflammation.

Methods We investigated the potential of LXA4 and a synthetic LX analog (Benzo-LXA4)astherapeutics 2 2 in a murine model of diabetic kidney disease, ApoE / mice treated with streptozotocin. Results Intraperitoneal injection of LXs attenuated the development of diabetes-induced albuminuria, mesangial expansion, and collagen deposition. Notably, LXs administered 10 weeks after disease onset also attenuated estab- lished kidney disease, with evidence of preserved kidney function. Kidney transcriptome profiling defined a diabetic signature (725 ; false discovery rate P#0.05). Comparison of this murine signature with that of human diabetic kidney disease identified shared renal proinflammatory/profibrotic signals (TNF-a,IL-1b,NF-kB). In diabetic mice, we identified 20 and 51 transcripts regulated by LXA4 and Benzo-LXA4, respectively, and pathway analysis identified established (TGF-b1, PDGF, TNF-a,NF-kB) and novel (early growth response–1 [EGR-1]) networks acti- vatedindiabetes andregulatedby LXs.Inculturedhuman renal epithelial cells, treatment with LXs attenuated TNF-a–driven Egr-1 activation, and Egr-1 depletion prevented cellular responses to TGF-b1 and TNF-a. Conclusions These data demonstrate that LXs can reverse established diabetic complications and support a therapeutic paradigm to promote the resolution of inflammation.

J Am Soc Nephrol 29: 1437–1448, 2018. doi: https://doi.org/10.1681/ASN.2017101112

Received October 19, 2017. Accepted January 23, 2018. Diabetes is recognized as a major epidemic, which has increased in incidence by 50% over E.P.B. and M.M. share first authorship. M.E.C., C.G. and P.K. share the past 15 years.1,2 Diabetic microvascular com- senior authorship. plications include kidney disease (nephropathy) Correspondence: Dr. Phillip Kantharidis, Department of Diabetes, as well as neuropathy and retinopathy.3 Diabetic Central Clinical School, Monash University, Clayton, VIC, Australia or Dr. Eoin Brennan, UCD Diabetes Complications Research Centre, kidney disease (DKD) is the leading cause of UCD Conway Institute of Biomolecular and Biomedical Research, UCD ESRD, affecting approximately 30% of patients School of Medicine and Medical Sciences, University College Dublin, with long-standing type 1 and type 2 diabetes, Ireland. Email: [email protected] or [email protected] and is characterized by proteinuria and gradual Copyright © 2018 by the American Society of Nephrology

J Am Soc Nephrol 29: 1437–1448, 2018 ISSN : 1046-6673/2905-1437 1437 BASIC RESEARCH www.jasn.org loss of kidney function.4,5 There is now a growing appreci- Significance Statement ation for the role of chronic low-grade inflammation as a common pathogenic mechanism. Evidence from clinical Impaired resolution of inflammation underlies chronic conditions, studies suggests that inflammatory markers including including microvascular complications of diabetes such as diabetic TNF-a, IL-1, IL-6, and monocyte chemoattractant kidney disease (DKD). Lipoxins (LXs) are lipid mediators that pro- mote the resolution of inflammation. Here, we investigated the 1 (MCP-1) are elevated in patients with diabetes (type 1 and potential of LXA4 and a synthetic LX analogue (Benzo-LXA4) as type 2), and that their levels may predict the onset and pro- therapeutics in a murine model of DKD (streptozotocin diabetic 2 2 gression of diabetic complications.6–11 ApoE / mouse). The development of diabetes-induced albumin- The failed resolution of inflammation may be a major uria, mesangial expansion, and collagen deposition was attenuated fi fi contributor to the pathogenesis of diabetes, CVD, and as- by LXs. Kidney transcriptome pro ling de ned a diabetic signature, and LX-mediated transcriptome responses. Using human renal 12–15 fi sociated complications. The identi cation of endoge- epithelial cells, we demonstrate that LXs attenuate Egr-1 activation. nous mediators that promote resolution, including lipids These data demonstrate for the first time that LXs can reverse es- and cytokines, provides a template for potential mimicry tablished diabetic complications and support a therapeutic para- and avoiding the complications associated with chronic digm to promote the resolution of inflammation. 12,16–25 anti-inflammatory approaches. Lipoxin A4 (LXA4) fl is an eicosanoid generated during acute in ammatory re- In Vitro Studies fl sponses that promotes the resolution of in ammation via Immortalized human kidney epithelial cells (HK-2; ECACC, the G-protein coupled formyl peptide receptor 2 Porton Down, UK) were cultured at 37°C in a humidified 19,26,27 (ALX/FPR2). Here, we have explored the potential of atmosphere of 95% air/5% CO2, and maintained in DMEM- LXA4 and a synthetic analog, Benzo-LXA4,tomodulate F12 (Sigma-Aldrich, Steinheim, Germany) supplemented with DKD in a murine model (streptozotocin [STZ]-treated 2 mM L-glutamine, 100 U/ml penicillin, 100 mg/ml streptomy- 2/2 ApoE mice). This model combines the genetic deletion cin, 10 ng/ml epidermal growth factor, 36 ng/ml hydrocortisone, of apo E, leading to hyperlipidemia, with STZ-mediated and 3 pg/ml triiodothyronine; and 5 mg/ml insulin, 5 mg/ml b pancreatic islet cell ablation, leading to diabetes, ulti- transferrin, and 5 ng/ml selenium solution (Sigma-Aldrich). Af- mately driving a more severe and accelerated renal in- ter serum restriction for 24 hours, cells were stimulated with ve- jury.28–36 We report that LXs attenuate the development hicle (0.1% ethanol), LXA4 (0.1 nM), or Benzo-LXA4 (1 nM) for of proteinuria and glomerular injury in diabetic mice. 30 minutes and media was removed and replaced with media with Most noteworthy are our data that show that LXs reverse or without TGF-b1(10ng/ml;PromoCellGmbH). established renal damage. We have investigated the under- lying mechanisms for these responses via high-throughput fi sequencing of renal tissue and have identified specific Renal RNA-Seq Pro ling networks of induced by diabetes and sus- Detailed methods are available on RNA-seq and bioinfor- fl ceptible to regulation by LXs including Egr-1. matic analysis in the Supplemental Material. Brie y, RNA was isolated from kidney Trizol homogenates using the Direct-zol RNA MiniPrep Kit (Zymo Research; n=6 kid- METHODS neys per treatment group). Normalized read counts for all genes in all samples are detailed in Supplemental Table 9. Tran- , In Vivo Preclinical Studies scripts with a false discovery rate (FDR) P value 0.05 were 2 2 fi Six-week-old ApoE / male mice (C57BL/6 background) deemed statistically signi cant. Upstream regulator analysis of were rendered diabetic by five daily intraperitoneal (ip) differentially expressed gene sets was performed using the Inge- injections of STZ (Sigma-Aldrich, St Louis, MO) at a nuity Pathway Analysis Z-score algorithm (Qiagen). Analysis of 2 2 dose of 55 mg/kg. ApoE / mice were administered either promoters for enriched TFBSs was performed using Genomatix Matbase (Genomatix). RNA-seq data are deposited at the Gene ethanol (0.1%), LXA4 (5 mg/kg;Merck,Calbiochem),or Expression Omnibus (GSE107942). Benzo-LXA4 (1.7 mg/kg; synthesized at University College Dublin, Ireland37) twice weekly by ip injection. For the prevention study design, mice were followed for 10 or Statistical Analyses 20 weeks, and were administered ethanol, LXA4,or All statistical analyses were performed utilizing GraphPad Benzo-LXA4 between weeks 1 and 10 or weeks 1 and 20, Prism software. Experiments with only one treatment were respectively. For the intervention study design, mice were assessed by t test. Experiments with multiple treatment followed for 16 weeks, and were administered ethanol, groups were analyzed by one-way ANOVAwith post hoc com- LXA4, or Benzo-LXA4 between weeks 10 and 16. Blood glu- parisons of group means performed by Fisher’s least signifi- cose levels were monitored weekly after STZ injections cant difference method. A P value #0.05 was considered for the duration of the studies to confirmthediabeticsta- statistically significant. Significance between groups is indi- tus of these mice. Detailed methods are available in the cated for each figure. Unless otherwise specified, data are Supplemental Material. shown as mean6SEM.

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2/2 Table 1. Metabolic data for ApoE mice with and without diabetes treated with LXA4 or Benzo-LXA4

ApoE KO+Vehicle ApoE KO+LXA4 ApoE KO+Benzo-LXA4 Nondiabetic Diabetic Nondiabetic Diabetic Nondiabetic Diabetic 10 wk progression study: LXA4 or Benzo-LXA4 treatment, weeks 1–10 Plasma glucose, mmol/L 10.760.4 28.261.2a 10.560.3 27.561.2a 11.161.3 29.260.8a Glycated Hb, % 4.860.1 10.060.9a 4.760.1 10.160.8a 4.460.1 9.760.8a Systolic BP, mm Hg 108.060.31 109.060.73 108.060.21 108.060.69 109.060.76 109.060.27 Body weight, g 30.260.5 24.260.6a 29.760.6 23.860.6a 29.960.3 24.960.7a Kidney weight, g 0.1960.003 0.2160.006a 0.1960.006 0.2060.006 0.2060.006 0.2060.006 Kidney/body weight, % 0.660.01 0.960.02a 0.660.02 0.860.03a,b 0.760.02 0.860.02a,b Urinary albumin, mg/24 h 11.361.5 33.864.1a 12.363.3 21.363.7a,b 9.162.2 27.166.7a Creatinine clearance, ml/min 0.2160.06 0.2660.02 0.1560.04c 0.1960.04b 0.1260.02c 0.1460.02b Creatinine clearance, ml/min per m2 14.162.3 31.262.6a 16.564.4 19.162.5b 12.661.9 15.762.3b

20 wk progression study: LXA4 or Benzo-LXA4 treatment, weeks 1–20 Plasma glucose, mmol/L 10.160.2 28.760.7a 10.160.2 30.060.6a 10.060.1 29.460.7a Glycated Hb, % 4.360.1 11.060.7a 4.660.1 11.960.7a 4.760.1 10.360.9a Systolic BP, mm Hg 108.060.38 109.060.55 108.060.21 107.060.66 108.0673 109.060.27 Body weight, g 29.960.5 25.860.8a 30.660.7 23.860.9a 31.060.6 24.760.8a Kidney weight, g 0.1960.005 0.2160.006a 0.2060.006 0.2360.008a 0.2060.005 0.2260.005a Kidney/body weight, % 0.660.01 0.860.03a 0.660.01 0.960.03a 0.660.01 0.860.03a Urinary albumin, mg/24 h 17.662.8 84.0620.9a 14.062.8 58.5611.0a 18.162.8 33.764.8a,b Creatinine clearance, ml/min 0.1560.02 0.2060.02a 0.1660.03 0.1960.02 0.1860.02 0.3360.07a,b Creatinine clearance, ml/min per m2 15.862.3 24.961.9a 16.563.1 21.062.7 19.761.9 38.467.4a

16 wk intervention study: LXA4 or Benzo-LXA4 treatment, weeks 10–16 Plasma glucose, mmol/L 10.160.2 31.460.7a 9.860.1 29.460.9a 9.760.2 31.860.4a Glycated Hb, % 4.660.13 11.860.5a 4.460.1 11.560.7a 4.760.2 10.761.0a Systolic BP, mm Hg 109.060.61 109.060.71 110.060.83 109.060.44 109.060.72 108.060.71 Body weight, g 32.961.0 23.460.9a 31.560.6 23.760.6a 31.960.3 24.360.9a Kidney weight, g 0.2160.008 0.2060.008 0.2160.007 0.2160.006 0.2160.006 0.2060.007 Kidney/body weight, % 0.660.03 0.960.02a 0.760.02 0.960.04a 0.660.01 0.860.03a Urinary albumin, mg/24 h 13.961.4 25.162.1a 15.261.9 17.362.4b 15.161.6 21.362.9a Data are shown as mean6SEM. n=8–12 per group. KO, knockout; Hb, haemoglobin. aANOVA P,0.05 versus nondiabetic. bANOVA P,0.05 versus diabetic ApoE KO+Vehicle. cANOVA P,0.05 versus nondiabetic ApoE KO+Vehicle.

2 2 RESULTS albumin in diabetic ApoE / mice at 10 weeks and 20 weeks, and we provide evidence of reduced albuminuria 2/2 LXs Prevent the Development of Diabetes-Associated in diabetic ApoE mice that received LXA4 at 10 weeks Kidney Disease (Table 1) and Benzo-LXA4 at 20 weeks (Table 1). Further- We induced diabetes mellitus using low-dose STZ in more, renal hypertrophy (kidney/body weight ratio) in 2 2 2 2 ApoE / mice, which were followed for 10–20 weeks to allow diabetic ApoE / mice was elevated in comparison with 2 2 development of moderate (10 weeks) and severe (20 weeks) nondiabetic control ApoE / mice, and this effect was at- 2 2 kidney disease. In keeping with our previous investigations tenuated in 10-week diabetic ApoE / mice treated with using LXA4 or Benzo-LXA4, we observed no evidence of - LXs (Table 1). icity or increased mortality in administered LXs. All At 20 weeks, diabetes-induced glomerular expansion and diabetic animals had elevated blood glucose and glycated mesangial matrixexpansionwere significantly attenuated by hemoglobin levels in comparison with their nondiabetic con- LXs, as assessed by periodic acid–Schiff staining (Figure 1, A 2 2 trols. Diabetic ApoE / mice exhibit renal hyperfiltration, as and B). Similarly, Masson’s trichrome staining indicated an evidenced by increased creatinine clearance (Table 1). LXA4 increase in extracellular matrix accumulation in diabetic 2/2 and Benzo-LXA4 attenuated diabetes-induced increases in ApoE mice at 20 weeks. Interestingly, LXA4,butnot creatinine clearance at 10 weeks (Table 1). This protection Benzo-LXA4, attenuated extracellular matrix accumulation 2 2 was also evident at 20 weeks, with no significant increase in in diabetic ApoE / mice (Supplemental Figure 1). Dia- 2 2 2 2 creatinine clearance between control and diabetic ApoE / betic ApoE / mice at 10 weeks showed evidence of en- mice that received LXA4. There was also increased urinary hanced fibrotic responses: increased expression of genes

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LXs Reverse Established Diabetes- Associated Kidney Disease Given the observations that LXs could at- tenuate the development of kidney disease we then investigated whether LXs could affect established disease. Diabetes was in- duced by STZ, and treatment with LXs in- troduced at 10 weeks for an additional 6 weeks (16-week intervention study). At 2 2 16 weeks, diabetic ApoE / mice presen- ted with significantly elevated urinary albumin, and LXA4 treatment attenuated albuminuria (Table 1). Diabetes-induced glomerular expansion and mesangial matrix expansion were significantly attenuated by LXs, as assessed by periodic acid–Schiff staining (Figure 2, A and B). Immunohistochemical staining of collagen IV in glomeruli indicated that LXA4 treat- ment significantly reduced collagen IV ex- pression (Figure 2, C and D). LX treatment significantly attenuated gene expression of markers of fibrosis in diabetic mice, includ- ing col1a1, Fibronectin (fn1), a-sma, ctgf, tgf-b,andvegf (Figure 2, E and F). Simi- larly, the gene expression levels of known inflammatory mediators (vcam-1, mcp-1, tnf-a, nf-kb, il-1b, il-6, il-10, cd204, arg1, inos)weresignificantly reduced after LX treatment.

Renal Transcriptome Profiling Identifies LX-Regulated Transcriptional Networks Tofurther understand the molecular mech- Figure 1. LXs attenuate DKD. (A) Structure of endogenous LXA4 and Benzo-LXA4 anisms underlying renal complications of and study design overview. ApoE2/2 mice were rendered diabetic by STZ, and a diabetes and the effects of LXs, we investi- subgroup of diabetic and nondiabetic ApoE2/2 mice were administered ethanol m m gatedglobalgeneexpressioninkidneys (0.1%), LXA4 (5 g/kg), or Benzo-LXA4 (1.7 g/kg) twice weekly ip from weeks 1 to 2/2 10 (10-week prevention study) or weeks 1 to 20 (20-week prevention study). (B and from control and diabetic ApoE mice C) Paraffin-embedded kidney sections of 20-week diabetic and control ApoE2/2 administered vehicle (ethanol (0.1%), mice administered ethanol (0.1%), LXA4, or Benzo-LXA4 from weeks 1 to 20 were LXA4, or Benzo-LXA4 from weeks 1 to 10 stained by periodic acid–Schiff stain. Quantification of the glomerulosclerosis in- (n=6 per treatment group). After data fil- jury index is shown in the bar graph as mean6SEM (n=8–10/group; *P,0.05; tering and normalization, 725 genes were **P,0.01). (D) Gene expression analysis of markers of kidney damage in kidney differentially expressed between con- 2 2 cortex tissue isolated from 10-week diabetic and nondiabetic ApoE2/2 mice trol and diabetic ApoE / mice (FDR administered vehicle, LXA4, or Benzo-LXA4. Expression was normalized to 18S for # 2 2 P 0.05) (Figure 3A, Supplemental Figure 2, gene expression analysis (n=8–10, 6SEM; *P#0.05 versus ApoE / +vehicle; 2 2 Supplemental Table 1). Here, there was fP#0.05 versus Diabetic ApoE / +Vehicle). KO, knockout; qPCR, quantitative notably greater expression of fn1, col4a1, polymerase chain reaction. vcam1, gremlin (grem1), sulf2, trp53inp1, mgmt, cdkn1a,andeda2r,andacorre- sponding decrease in cyp2d12 expression encoding collagen (col1, col3, col4), a–smooth muscle in diabetic kidneys (Figure 3B). The observed increase in (a-sma), connective tissue growth factor (ctgf), tgfb1, icam- expression of the bone morphogenetic antagonist grem1 in di- 1, vcam-1, mcp1, il-6, il-1b,andtnf-a,incomparisonwith abetic kidneys is consistent with our previous studies identify- 2 2 nondiabetic ApoE / control mice (Figure 1C). ing Gremlin as an important mediator of DKD.38,39

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2 2 Figure 2. LXs reverse established DKD. (A) Study design overview. ApoE / mice were rendered diabetic by STZ and diabetes was allowed 2/2 to progress for 10 weeks, after which a subgroup of diabetic and nondiabetic ApoE mice were administered ethanol (0.1%), LXA4 (5 mg/kg), or Benzo-LXA4 (1.7 mg/kg) twice weekly ip from weeks 10 to 16. (B and C) Paraffin-embedded kidney sections of 16-week in- 2/2 tervention study diabetic and control ApoE mice administered ethanol (0.1%), LXA4, or Benzo-LXA4 from weeks 10 to 16 were stained by periodic acid–Schiff stain. Quantification of the glomerulosclerosis injury index is shown in the bar graph as mean6SEM (n=8–10/group; *P,0.05; **P,0.01; ***P,0.001). (D and E) Immunohistochemical staining of collagen IV in glomeruli of paraffin-embedded kidney sections 2/2 of 16-week intervention study diabetic and control ApoE mice administered ethanol (0.1%), LXA4, or Benzo-LXA4 from weeks 10 to 16. Quantification of staining is shown in the bar graph as mean6SEM (n=8–10/group; *P,0.05). Gene expression analysis of markers of (F) 2 2 kidney fibrosis and (G) inflammation in kidney cortex tissue isolated from 16-week diabetic and nondiabetic ApoE / mice administered vehicle, LXA4, or Benzo-LXA4 from weeks 10 to 16. Expression was normalized to 18S for gene expression analysis (n=8–10, 6SEM; *P#0.05 2 2 f 2 2 versus ApoE / +vehicle; P#0.05 versus Diabetic ApoE / +Vehicle). KO, knockout; qPCR, quantitative polymerase chain reaction.

Comparison of transcriptome profiles in control and diabetic glomerular and tubular transcriptome profiles was investi- 2 2 ApoE / mice identified several enriched upstream regulators gated (Supplemental Figure 5).42 Upstream regulator enrich- predicted to be activated or repressed in diabetic kidneys. ment analysis identified a cohort of regulators predicted to be Among these, the activity of TNF-a, IL-6, NF-kB, TGF-b, activated or repressed in human diabetic kidneys (Z-score $2 VEGF, and PDGF is enhanced in the diabetic kidney (Z-score or #22), and the activation of these regulators was next de- 2 2 $2or#22; Figure 3C, Supplemental Table 2). termined in the diabetic ApoE / kidney. Hierarchic cluster- Because these transcriptomic data are derived from whole ing analysis of enriched regulators in human and murine DKD kidney cortex, we performed an analysis of cell type–specific tissue identified coregulated networks (Supplemental Figure expression profiles within the cluster of 725 genes identified 6). Noteworthy among the coregulated activators, there was as differentially expressed between control and diabetic evidence of increased activity of TNF-a, NF-kB, IL-1b, and 2 2 ApoE / mice. We first performed a basic glomerular versus EGR-1 in diabetic tissues. Hierarchic clustering analysis of 2 2 tubule compartment analysis using published microarray data 268 known NF-kB targets expressed in ApoE / kidneys indi- from healthy human kidneys,40 with no bias seen toward a cates that there is clustering of nondiabetic and diabetic specific compartment (Supplemental Figure 3). Using gene kidneys on the basis of the expression of these genes (Supple- profiles from each of 14 renal tubule segments along the mental Figure 6). We also note evidence of reduced activation proximal tubule,41 we identified segment-specificprofiles of the let-7 micro-RNA family in human and mouse diabetic (Supplemental Figure 4). tissues, which is in keeping with our previous studies implicat- Theoverlapofthemolecularsignatureofthediabetic ing loss of the let-7 miRNA family in renal fibrosis and also 2 2 ApoE / kidney with publicly available human DKD diabetes-associated atherosclerosis.43–45

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2 2 Figure 3. Transcriptome profiling identifies the networks associated with kidney disease in the diabetic ApoE / mouse model. (A) Venn diagram indicating number of significant differentially expressed transcripts (FDR P value ,0.05) between diabetic and control 2/2 ApoE mice administered ethanol (0.1%), LXA4,orBenzo-LXA4 from weeks 1 to 10. (B) Renal expression levels of fn1, col4a1, grem1, vcam1, cyp2d12, trp53inp1, sulf2, mgmt, cdkn1a,andeda2r genes in control and diabetic mice administered ethanol (0.1%) (n=5–6 per group; FDR P value ,0.05 for all transcripts). (C) Upstream regulators expected to be increased or decreased between control and 2 2 diabetic ApoE / mice administered ethanol. Regulators were identified using the IPA regulation Z-score algorithm according to gene expression changes. A positive or negative Z-score value indicates that a function is predicted to be increased (red color) or decreased

(blue color), respectively. Corresponding 2Log2 P values indicate whether there is a statistically significant overlap between the dataset genes and genes that are known to be regulated by the upstream regulator. All regulators represented on the graph are significantly enriched (Z-score $2or#22; P,0.05). GPCRs, G-protein coupled receptors; vs, versus.

2/2 Comparison of transcriptome profiles of diabetic ApoE administered LXA4 (Figure 4A, Supplemental Table 3). Simi- 2/2 mice administered vehicle versus LXs identified several master larly, in diabetic ApoE mice administered Benzo-LXA4, regulators and transcripts modulated by LXs. Here, upstream there is reduced activation of PDGF, TNF-a,andTGF-b sig- regulator analysis predicts repression of NF-kB, TNF-a, naling networks (Figure 4B). Differential expression analysis 2 2 2 2 PDGF, and IL-6 activity in diabetic ApoE / mice between treatment groups in diabetic ApoE / mice

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Figure 4. Analysis of renal transcriptome responses identifies LX-regulated transcriptional networks. (A and B) Upstream regulator 2 2 analysis of transcriptome data identifies regulators predicted to be changed between diabetic ApoE / mice administered ethanol versus (A) LXA4 or (B) Benzo-LXA4 treatment from weeks 1 to 10. Regulators were identified using the IPA regulation Z-score algorithm according to gene expression changes. A positive or negative Z-score value indicates that a function is predicted to be increased (red color) or decreased (blue color), respectively. Corresponding 2Log2 P values indicate whether there is a statistically significant overlap between the dataset genes and genes that are known to be regulated by the upstream regulator. All regulators represented on the graph are significantly enriched (Z-score $2or#22; P,0.05). (C and D) Heatmaps of normalized gene expression indicating transcripts displaying significant differential expression (FDR P value ,0.05) between diabetic mice administered ethanol (0.1%) versus LXA4 or Benzo-LXA4 from weeks 1 to 10. Expression levels range from blue (low expression) to red (high expression). (E) Box plots indicating expression of genes regulated by both LXA4 and Benzo-LXA4 (,adamtsl3, ngef, lamb3, grem1,andnr4a1). Transcript abundance across all treatment group is shown (*FDR P value ,0.05). ID, identifier.

identified 20 and 51 transcripts regulated by LXA4 and Benzo- factor binding sites within the promoters of the 2/2 LXA4, respectively (FDR P#0.05; Figure 4, C and D, Supple- 725 differentially expressed genes in the diabetic ApoE mental Tables 4 and 5). mouse kidney. Here, we noted a significant enrichment of binding sites for several transcription factors, including LXs Regulate the Egr-1 Transcriptional Network in Egr-1 (Z-score=12.74) (Figure 5A, Supplemental Table 6). In- Diabetic Kidneys terestingly, an analysis of the promoters of genes that were Transcriptome data indicates that the expression of the tran- modulated by LXA4 (n=20) and Benzo-LXA4 (n=51) also scription factor early growth response–1(egr-1) is increased in identified a significant over-representation of Egr-1 binding 2 2 the diabetic ApoE / kidney, and this is prevented by LX sites within these genes, suggesting that LXs may act via tar- 2 2 treatment (Figure 4E). Recent studies suggest that Egr-1 / geting the Egr-1 downstream network (Figure 5A, Supple- mice are protected from kidney disease in a model of tubu- mental Table 6). lointerstitial nephritis, with attenuated renal proximal tubule Analysis of the expression of predicted Egr-1–regulated injury and NF-kB activity evident.46 To expand on these data, genes was performed in publicly available expression data we determined whether there was an enrichment for specific from human DKD tissue,42 identifying 155 Egr-1 target genes

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Figure 5. LXA4 regulates the Egr-1 transcriptional network in renal epithelial cells. (A) Heatmap of over-represented 2 2 binding sites (TFBSs) in promoters of genes identified to be differentially expressed between nondiabetic and diabetic ApoE / mice administered ethanol, and also between diabetic mice ApoE2/2 mice administered ethanol versus LXA4 or Benzo-LXA4. Enriched TFBSs were identified using the Genomatix Z-score algorithm, with a positive Z-score (red color) indicative of TFBS enrichment. All regulators represented on the graph are significantly enriched in at least one comparison (Z-score $2; P,0.05). (B) Egr-1 gene expression levels in human renal proximal tubule epithelial cells (HK-2) after TNF-a (1 ng/ml), TGFb (5 ng/ml), and LXA4 treatment (0.1 nM; 30 minutes). (C) Gene expression of Egr-1 after siRNA treatment targeting Egr-1 in HK-2 cells. (D) Gene expression of markers of TNF-a signaling ac- tivation in HK-2 cells after TNF-a treatment (1 ng/ml; 24 hours) in the presence/absence of nontargeting scrambled siRNA or Egr-1 siRNA.

(E) TNF-a gene expression levels in HK-2 cells after TNF-a (1 ng/ml) and LXA4 (0.1 nM) treatment. (F) Gene expression of markers of TGFb signaling activation in HK-2 cells after TGFb treatment (5 ng/ml; 24 hours) in the presence/absence of nontargeting scrambled siRNA or Egr-1 siRNA. (G) Representative western blot and corresponding densitometry analysis of protein expression levels of markers of TGFb signaling activation in HK-2 cells after TGFb treatment (5 ng/ml; 24 hours) in the presence/absence of nontargeting scrambled siRNA or Egr-1 siRNA. Expression was normalized to Gapdh for gene expression analysis and b-actin for protein expression (n=3–4, 6SEM). *P#0.05. qPCR, quantitative polymerase chain reaction; siRNA, short-interfering RNA; vs, versus. differentially expressed between patients with DKD and diabetic tissues, including alox5, dclk1, col4a1, col4a2, vim, 2 2 healthy controls (P#0.05; Supplemental Figure 8). The ex- and . After LX treatment in diabetic ApoE / mice the pression of the Egr-1–regulated subset was then determined expression of these genes was suppressed. These data indicate 2 2 in the ApoE / kidneys RNA-seq dataset, and also compared that Egr-1 targets are dysregulated in human and murine against published transcriptomics data from renal tissue of DKD, and LXs may regulate this transcriptional network. three additional mouse models of diabetes (STZ DBA/2, We next sought to further investigate a mechanistic link C57BLKS db/db, and eNOS-deficient C57BLKS db/db between LXA4 and Egr-1 in human renal cells. Previous stud- mice).47 Interestingly, unsupervised hierarchic clustering ies have indicated that primary induction of Egr-1 is observed analysis of the Egr-1–regulated subset on the basis of expres- within the proximal tubule,46,48,49 and we have previously sion data from human and murine DKD tissues identifies a characterized the transcriptome of immortalized human renal group of genes coregulated in human and mouse model proximal tubule (HK-2) cells, with evidence of Egr-1

1444 Journal of the American Society of Nephrology J Am Soc Nephrol 29: 1437–1448, 2018 www.jasn.org BASIC RESEARCH expression in these cells.50 Comparison of the HK-2 transcrip- nificantly reduce the global health burden associated with di- tome with microdissected renal tubule RNA-seq data indicates abetes and related complications. We have shown for the first that the profile of this cell line largely represents what is ob- time the protective effects of LXs on kidney disease in a murine served in the renal tubule, with evidence of expression of genes model of STZ‐induced diabetes. In addition to endogenous encoding key junctional , indicating an epithelioid LXA4, we evaluated the therapeutic potential of a synthetic (Supplemental Figure 8, Supplemental Table 7). (1R)-stereoisomer analog (Benzo-LXA4), generated through Metabolically, HK-2 cells express genes encoding the enzymes modification of the LXA4 triene unit. Although our previous responsible for arginine synthesis and fructose conversion to in vivo studies demonstrated a degree of protective effect for glucose, all important metabolic functions of the proximal LXs in other experimental models of renal disease including tubule. They express some but not all gene-encoding enzymes unilateral ureteric obstruction,37,53 it is critical to examine its involved in the ammoniagenic pathway, and they also role in the most common cause of ESRD, diabetes, which now express a different set of lactate transporters than native prox- comprises more than 50% of individuals on renal replacement imal tubule cells. Interestingly, on the basis of our transcrip- programs worldwide. In this study, the Benzo-LXA4 analog tome data, these cells do not robustly express Megalin (lrp2), exerted similar actions to LXA4,andinsome,butnotall, hnf4a, and -1 (aqp1), and they express a set of clau- contexts proved more effective than the native compound. dins that are more characteristic of downstream segments. We have previously reported that, in this model, after Finally, whereas HK-2 cells express transcripts for major apical 10 weeks of diabetes there is increased expression of genes related transporters sglt1 and napi-2, transcripts for several trans- to fibrosis and inflammation as well as increased albuminuria porters involved in sulfate transport or organic ion transport and podocyte effacement, reflecting all markers of early DKD. are not detectable. Therefore, as is the case with many immor- After 16–20 weeks of diabetes, there is evidence of structural talized cell lines, these cells do not express all genes associated changes, including mesangial expansion, thickening of the with the healthy native tubule, and it is important to recognize glomerular basement membrane, and tubulointerstitial fibro- this limitation when designing experiments and interpreting sis, reflecting a more advanced stage of DKD.28–34,36,54–56 data. However, it is important to acknowledge that no model reca- We performed time-course experiments using HK-2 cells pitulates all functional, structural, and molecular pathologic 57–60 pretreated with LXA4 (30 minutes; 1 nM) followed by TGF-b features of human DKD. In this study, diabetes was asso- (5 ng/ml) or TNF-a (1 ng/ml) treatment for up to 24 hours. ciated with kidney injury, as evidenced by increased kidney/ Enhanced Egr-1 expression was observed 30 minutes post– body weight ratio, hyperfiltration, and albuminuria, typifying TNF-a treatment, with maximal induction observed 1 hour DKD. Importantly, LXs suppressed diabetes-induced kidney after TNF-a treatment (Figure 5B). This TNF-a–mediated injury, as evidenced by reduced albuminuria. LXs attenuated induction of Egr-1 was significantly attenuated by LXA4 (Fig- the increase in kidney/body weight ratio observed in diabetic ure 5B). Egr-1 levels were unchanged in response to TGF-b.To animals. LXs also attenuated glomerular expansion and me- determine the consequences of depleted Egr-1 levels in renal sangial matrix deposition. These data are consistent with our epithelial cells we performed siRNA experiments targeting previous studies demonstrating that LXs can attenuate high-fat Egr-1 (Figure 5C). After Egr-1 depletion, we observed a sig- diet–induced kidney disease, and experimental tubuloin- nificant attenuation of Tnf-a gene expression in response to terstitial fibrosis induced by unilateral ureteric obstruc- 37,53 TNF-a treatment (Figure 5D), and confirmed that LXA4 can tion. Furthermore, our data also highlight the potential 2 2 modulate Tnf-a gene expression in renal epithelial cells (Fig- of LXs to reverse established CKD in diabetic ApoE / mice, ure 5E). Despite the fact that TGF-b treatment of renal epi- with renoprotective effects observed in those mice adminis- thelial cells did not lead to any direct upregulation of Egr-1 tered LXs for 6 weeks, commencing after 10 weeks of diabetes. expression (Figure 5B), after Egr-1 depletion there was an at- This is relevant to the clinical context where diabetic subjects tenuated induction of collagen type 1 (Col1a1) and fibronectin often present with evidence of renal disease, as reflected by (Fn1)byTGF-b (Figure 5, F–H), implicating Egr-1 as a down- albuminuria. stream effector in the TGF-b pathway. This is in keeping with To expand on our understanding of the renoprotective ef- previous studies implicating Egr-1 in the regulation of Col1a1 fects of LXs, global transcriptome profiling was performed. and Fn151,52 and evidence that LX modulates expression of Using this approach, a large cohort of transcripts were iden- Col1a1 and Fn1 in renal epithelia.43 Taken together, these re- tified as differentially expressed between control and diabetic sults suggest that LXs act to suppress the Egr–1 network in mouse tissue. Importantly, analysis of these transcripts pro- DKD. vides evidence of activation of key regulatory networks impli- cated in the pathogenesis of human DKD, including TNF-a, IL-6, NF-kB, TGF-b, VEGF, and PDGF. This is an important DISCUSSION observation because it clearly demonstrates the strength of this mouse model to mimic key facets of human disease. Analyses Pharmacologic strategies promoting the resolution of inflam- of transcriptional responses to LXs in the diabetic kidney mation represent a novel therapeutic paradigm that could sig- suggest a repression of TNF-a,IL-1B,PDGF,NF-kB, and

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TGF-b regulatory networks. These confirm our previous find- and A.E.-O. performed the experimental work and acquired and an- ings in renal mesangial and epithelial cells demonstrating that alyzed the data. S.T.A.-S. and P.G. designed and synthesized the Benzo- LXs attenuate responses of these cells to growth factors such as LXA4 analogue. All authors reviewed and approved the manuscript. PDGF via ALX/FPR2-mediated receptor kinase acti- vation and TGF-b via let-7 miRNA targeting of TGFb- receptor, type 1.43,61 Considering the limitation of bulk tissue DISCLOSURES RNA-seq, future studies will be required to determine indi- None. vidual cell type responses to the setting of diabetes and also the LXs. Expression of the Egr zinc finger transcription factor Egr-1 was upregulated in the diabetic kidney, and reduced REFERENCES by both LXA4 and Benzo-LXA4. Egr-1 is part of the immedi- ate-early gene (IEG) network, which are rapidly activated via 1. 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Detailed Methods

In Vivo Preclinical Studies Animals were housed at the Baker IDI Heart and Diabetes Research Institute and studied according to National Health and Medical Research Council (NHMRC) guidelines in line with international standards. Animals had unrestricted access to water and feed, and were maintained on a 12 hour /dark cycle on standard mouse chow (Barastoc; Ridley Agriproducts, St Arnaud, VIC, Australia). Six-week-old ApoE−/− male mice (C57BL/6 background) were rendered diabetic by 5 daily intraperitoneal (I.P.) injections of streptozotocin (Sigma-Aldrich, St Louis, MO) at a dose of 55 mg/kg. ApoE−/− mice were administered either ethanol (0.1%), LXA4 (5 ug/kg; Merck, Calbiochem) or Benzo-LXA4 (1.7 ug/kg; synthesized at University College Dublin, Ireland 1 twice weekly by I.P injection. For the prevention study design, mice were followed for 10 weeks (moderate disease) or 20 weeks (severe disease), and were administered ethanol, LXA4, or Benzo-LXA4 between weeks 1-10 or weeks 1-20, respectively. For the intervention study design, mice were followed for 16 weeks, and were administered ethanol, LXA4, or Benzo-LXA4 between weeks 10-16. Blood glucose levels were monitored weekly after STZ injections for the duration of the studies to confirm the diabetic status of these mice. Only animals with a blood glucose level >15 mmol/l 1 week after the induction of diabetes were included in the study. Ten weeks post induction of diabetes systolic blood pressure was assessed by non-invasive tail cuff system in conscious mice. Urine samples were collected in metabolic cage for 24 hours before the end of the experiment. Glycated haemoglobin (HbA1c) was measured using the Cobas Tina-quant® HbA1c Gen. 3 assay (Roche Diagnostics, VIC, Australia), and creatinine in blood and urine was analysed using the COBAS INTEGRA 400 PLUS (Roche Diagnostics, VIC, Australia), as per the manufacturers guidelines. Total glucose was measured in plasma with a standard commercial enzymatic assay (Beckman Coulter Diagnostics, Gladsville, NSW, Australia). Albumin in urine was measured using the Mouse Albumin ELISA Quantitation Set (Bethyl Laboratories Inc., Montgomery, TX). At study end-point, animals were anaesthetised by sodium pentobarbitone IP (100 mg/kg body weight; Euthatal, Sigma-Aldrich, Castle Hill, NSW, Australia) and organs were rapidly dissected.

In Vitro Studies Immortalized human kidney epithelial cells (HK-2; ECACC, Porton Down, UK) were cultured at 37°C in a humidified atmosphere of 95% air/5% CO2 , and maintained in DMEM-F12 (Sigma-Aldrich, Steinheim, Germany) supplemented with 2 mM L-glutamine, 100 U/ml penicillin, 100 mg/ml streptomycin, 10 ng/ml endothelial growth factor, 36 ng/ml hydrocortisone, 3 pg/ml triiodothyronine, and 5 mg/ml insulin, 5 mg/ml transferrin, and 5 ng/ml selenium (ITS) solution (Sigma-Aldrich). After serum restriction for 24 hours, cells were stimulated with vehicle (0.1% ethanol), LXA4 (0.1 nM; Merck, Calbiochem), or Benzo-LXA4 (1nM) for 30 minutes and media was removed and replaced with media with or without TGF-β1 (10 ng/ml; PromoCell GmbH).

Gene expression Analyses by Reverse Transcriptase Quantitative PCR RNA was extracted from mouse kidney tissue and HK-2 cells using TRIzol (Ambion). DNase treatment and cDNA synthesis were performed as previously described.2 Gene expression was determined utilizing TaqMan reagents (Life Technologies) with fluorescence signals being normalized to 18s rRNA or Gapdh utilizing the ddCT method. Probes and primers were designed using a Primer Express program and were purchased from Applied Biosystems (ABI, Foster City, CA, USA). Where no probes were used, Fast SYBR® Green mastermix was employed with gene specific primers. Primer and Probe sequences are detailed in Supplemental Table 8.

Protein Extraction and Western Blot Analyses Lysates were harvested in RIPA lysis buffer as previously described 3. Total protein was estimated using the Bradford assay. For Western blot analysis, antibodies used included the following: Beta-actin (1:20,000; Sigma-Aldrich), CDH1 (1:1,000; BD Biosciences, Oxford, UK), JAG1 (1:2,000; Santa Cruz Biotechnology, Santa Cruz, CA), FN1 (1:2,000; BD Biosciences), CTGF (1:1,000; Santa Cruz Biotechnology, Santa Cruz, CA). siRNA Transfections siGENOME SMARTpool Egr1 siRNA and siGENOME RISC Free control siRNA were purchased from Dharmacon. siRNAs were transfected into HK-2 cells at 60% confluence using Lipofectamine 2000 (Invitrogen, Carlsbad, CA) at a final concentration of 20 nM for 24 hours. Cells were then stimulated with TNF-α or TGF-β as previously described.

Histological and Immunohistochemical Staining Paraffin sections (4μm) of Kidney were used to stain for Masson’s Trichrome as described previously.4, 5 Briefly, 10 representative images per kidney section and single images of aortic arch, thoracic and abdominal aorta segments were quantitatively assessed in a blinded fashion. Quantification of all staining was determined using Image J software (http://imagej.net/Welcome).

Evaluation of Renal Pathologic Changes Paraffin-embedded sections of mouse kidney with a thickness of 3 μm were stained by Periodic acid–Schiff method, and the morphologic changes reflecting the pathologic injuries in glomeruli were evaluated in a blinded fashion in a quantitative manner. Briefly, 20 representative glomerular images at 40x magnification were taken for each section using a light microscope (BX43, Olympus Corporation, Shinjuku, Tokyo) and proportional area of mesangial expansion from PAS stained sections were measured using Image-Pro Analyser 7.0 (Media cybernetics, Rockville, MD). Quantification was determined using Image J software (http://imagej.net/Welcome).

Renal RNA-Seq Profiling RNA was isolated from kidney Trizol homogenates using the Direct-zol™ RNA MiniPrep Kit (Zymo Research; n=6 kidneys per treatment group). RNA quality was assessed by MultiNA Bioanalyzer (Shimadzu). Illumina HiSeq single end 100 cycle sequencing was performed at the Australian Genome Research Facility (AGRF, Melbourne). Reads were trimmed for quality using a minimum phred value of 20 and minimum length of 18 using Skewer.6 Reads were mapped with STAR to the mouse genome downloaded from Ensembl (GRCm38).7 Feature Counts was used to count reads mapped to gene bodies on the correct strand with a minimum mapping quality of 20 using Ensembl genome annotation (Mus musculus.GRCm38.86.gtf).8 The resulting count matrix underwent differential analysis with the EdgeR package.9 Transcripts with a false discovery rate (FDR) P-value <0.05 were deemed statistically significant. RNA-seq data is deposited in GEO (GSE107942), and normalized read counts for all transcripts in all samples are available in Supplemental Table 9. Upstream regulator analysis of differentially expressed gene sets was performed using Ingenuity Pathway Analysis Z-score algorithm (Ingenuity Systems, Qiagen). Detailed information on Ingenuity Pathway Analysis is available at www.qiagen.com. Briefly, this analysis examines how many known targets of each transcription regulator (transcription factor, cytokine, enzyme etc..) are present in the RNA-seq dataset, and also compares their direction of change. Relationships between molecules are supported by at least one reference from the literature, from a textbook, or from canonical information stored in the Ingenuity Knowledge Base. For each transcriptional regulator there are two statistical measures: an overlap p-value and an activation z-score. The overlap p-value measures whether there is a statistically significant overlap between the input dataset genes and the genes that are known to be regulated by a transcriptional regulator. It is calculated using a Fisher’s Exact Test, and significance is attributed to p-values <0.01. The activation z-score infers the activation state of the transcriptional regulator. This score is assigned based on changes in expression of genes identified in our RNA-seq dataset that are associated with a literature-derived regulation direction (i.e. activating or inhibiting). The statistical approach here is to define a quantity (z-score) that determines whether an upstream transcription regulator has significantly more ‘activated’ predictions than ‘inhibited’ predictions. A cut-off Z-score of ≥ 2 or ≤ −2 was deemed significant. Analysis of promoters for enriched TFBSs was performed using Genomatix Matbase (Genomatix). Promoter regions were defined as -1000bp/+100bp from transcription start site. Overrepresentations of TFBSs in promoters of differentially expressed genes was determined against a background population of murine promoters, with a cut-off Z-score ≥ 2 or ≤ −2 considered statistically significant. NF-κB target genes were downloaded from the NF-κB Transcription Factors Database (https://www.bu.edu/nf-kb/gene-resources/target-genes/). Heatmaps of differentially expressed genes were generated using Morpheus (Broad Institute, USA). Publicly available human DKD datasets were downloaded from Nephroseq (https://nephroseq.org/resource/login.html).

Statistics All statistical analyses were performed utilizing GraphPad Prism software. Experiments with only one treatment were assessed by Student’s t-test. Experiments with multiple treatment groups were analysed by one-way ANOVA with post-hoc comparisons of group means performed by Fisher’s least significant different method. A P-value ≤ 0.05 was considered statistically significant. Significance between groups is indicated for each figure. Unless otherwise specified, data are shown as mean ± S.E.M.

Supplemental Figures and Tables Fig. S1. Masson’s Trichrome staining for ECM accumulation in kidneys. Fig. S2. Smear plots for comparison of global gene expression in RNA-seq data from ApoE-/- mouse kidneys. Fig. S3. Compartment-specific expression of gene set differentially expressed in diabetic versus non- diabetic ApoE-/- kidneys. Fig. S4. Analysis of tubule compartment specific expression of gene set differentially expressed in diabetic versus non-diabetic ApoE-/- kidneys. Fig. S5. Comparison of transcriptional responses between human DKD and diabetic ApoE-/- model. Fig. S6. Expression of NF-κB target genes in ApoE-/- RNA-seq dataset. Fig. S7. LXs regulate the EGR1 transcriptional network in DKD. Fig. S8. Analysis of tubule compartment specific expression of genes identified as expressed in HK-2 renal tubule epithelial cells. Table S1. Differentially expressed genes between control and diabetic ApoE-/- mice. Table S2. Upstream regulator analysis: Control versus diabetic ApoE-/- mice. -/- Table S3. Upstream regulator analysis: Diabetic versus Diabetic + LXA4 or Benzo-LXA4 treated ApoE mice. -/- Table S4. Differentially expressed genes: Diabetic versus Diabetic + LXA4 treated ApoE mice. -/- Table S5. Differentially expressed genes: Diabetic versus Diabetic + Benzo-LXA4 treated ApoE mice. Table S6. TFBS promoter analysis of differentially expressed genes from ApoE-/- RNA seq experiment. Table S7. RNA-seq read counts for HK-2 cells in comparison with micro-dissected renal tubule compartments. Table S8. Details of primers and probes used for all quantitative PCR gene expression analysis. Table S9. Normalized read counts for RNA-seq dataset. Fig. S1. Masson’s Trichrome staining for ECM accumulation in kidneys.

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Fig. S1. (A) Masson’s Trichrome staining for ECM accumulation in kidneys of 20-week diabetic and control ApoE-/- mice administered ethanol (0.1%), LXA4 or Benzo-LXA4 and (B) Quantification of the staining is shown in the bar graph as mean ± SEM (n=8–10/group; *P<0.05).

Fig. S2. Smear plots for comparison of global gene expression in RNA-seq data from ApoE-/- mouse kidneys.

Non-diabetic ApoE-/- + EtOH Diabetic ApoE-/- + EtOH Diabetic ApoE-/- + EtOH

vs Diabetic ApoE-/- + EtoH vs Diabetic ApoE-/- + LXA4 vs Diabetic ApoE-/- + Benzo LX

Log Log FC

Log Log FC Log Log FC

Log CPM Log CPM Log CPM

Non-diabetic ApoE-/- + EtOH Non-diabetic ApoE-/- + EtOH Diabetic ApoE-/- + LXA4 Non-Diabetic ApoE-/- + LXA4

vs non-Diabetic ApoE-/- + LXA4 vs non-Diabetic ApoE-/- + Benzo-LX vs Diabetic ApoE-/- + Benzo-LX vs non Diabetic ApoE-/- + Benzo-LX

Log Log FC Log Log FC

Log Log FC Log Log FC

Log CPM Log CPM Log CPM Log CPM

*Each black point is a detected gene with non-significant changes in expression and red points are statistically significant (FDR<0.05). Log FC (Log2 fold-change); Log CPM (Log2 read-counts per million).

Fig. S3. Compartment-specific expression of gene set differentially expressed in diabetic versus non-diabetic ApoE-/- kidneys.

Fig. S3. Compartment-specific expression of gene set differentially expressed in diabetic versus non-diabetic ApoE-/- kidneys. Expression of 725 differentially expressed transcripts (identified in comparison of non-diabetic vs diabetic ApoE-/- mice) in micro-dissected healthy human kidneys (glomerular and tubule compartments). Human DKD microarray dataset was downloaded from Nephroseq (Lindenmeyer et al., PMID: 20634963). Red = higher expression; Blue = lower expression; Grey = no data available in human dataset for these genes.

Fig. S4. Analysis of tubule compartment specific expression of gene set differentially expressed in diabetic versus non-diabetic ApoE-/- kidneys.

Fig. S4. Analysis of tubule compartment specific expression of gene set differentially expressed in diabetic versus non-diabetic ApoE-/- kidneys. Expression of 725 differentially expressed transcripts (identified in comparison of non-diabetic vs diabetic ApoE-/- mice) in 14 compartments of microsdissected rat renal tubule. Rat renal tubule data was downloaded from (https://hpcwebapps.cit.nih.gov/ESBL/Database/NephronRNAseq/index.html) Lee JW et al., JASN 2015. PMID: 25817355. Red = higher expression; Blue = lower expression; Grey = no data available in rat tubule dataset for these genes. Terminology for nephron segments: S1, first segment of the proximal tubule; S2, second segment of the proximal tubule; S3, third segment of the proximal tubule; SDL, short descending limb of the loop of Henle; LDLOM, long descending limb of the loop of Henle in the outer medulla; LDLIM, long descending limb of the loop of Henle in the inner medulla; tAL, thin ascending limb of the loop of Henle; mTAL, medullary thick ascending limb of the loop of Henle; cTAL, cortical thick ascending limb of the loop of Henle; DCT, distal convoluted tubule; CNT, connecting tubule; CCD, cortical collecting duct; OMCD, outer medullary collecting duct; IMCD, inner medullary collecting duct.

Fig. S5. Comparison of transcriptional responses between human DKD and diabetic ApoE-/- model. Human DKD microarray dataset was downloaded from Nephroseq (Ju et al., PMID: 26631632). Genes that were significantly differentially expressed (FDR p<0.05) in renal tissue between DKD patients and healthy controls were selected. Glomerular (n=979 genes at FDR p<0.05) and Tubule (n=1233 genes at FDR p<0.05) compartments were analysed separately. Analysis was performed on the human DKD gene sets, as well as the differential gene sets from the ApoE-/- model (control versus diabetic; diabetic versus diabetic + LXA4, diabetic versus Benzo- LXA4). Upstream regulator analysis was performed using Ingenuity Pathway Analysis software for interrogation of differentially expressed gene lists for putative upstream regulators that drive the differential expression. Z-score is the output. This is an activation score (red = activated; blue = repressed; grey = no evidence of this regulator being activated or repressed). A cut-off of >2 or <-2 was used to select the strongest regulators (as recommended by IPA) in human DKD datasets. These were then assessed in the ApoE model.

Fig. S6. Expression of NF-κB target genes in ApoE-/- RNA-seq dataset.

Fig. S6. Expression of NF-κB target genes in ApoE-/- RNA-seq dataset. NF-κB target gene database (https://www.bu.edu/nf-kb/gene-resources/target-genes/) was used for identification of target genes. The expression of 268 NF-κB targets expressed in ApoE-/- kidney RNA-seq data was then determined. Hierarchical clustering analysis indicates that there is clustering of non-diabetic and diabetic kidneys based on the expression of these genes. Red = higher expression; Blue = lower expression; Grey = no data available in ApoE-/- RNA-seq dataset for these genes.

Fig. S7. LXs regulate the EGR1 transcriptional network in DKD.

Fig. S7. Expression of EGR1 targets was determined in published transcriptomic data from patients with DKD versus healthy controls, and also in three diabetes mouse models. Transcriptomic datasets were downloaded from Nephroseq. 10, 11 Predicted Egr1 target genes that were significantly differentially expressed (FDR p<0.05) in renal tissue between DKD patients and healthy controls were selected (n=155; FDR p<0.05) Heatmaps were generated of gene expression indicating transcripts displaying significant differential expression (FDR P-value <0.05). Red = upregulated; blue = downregulated; grey = no evidence of expression. Fig. S8. Analysis of tubule compartment specific expression of genes identified as expressed in HK- 2 renal tubule epithelial cells.

Fig. S8. Analysis of tubule compartment specific expression of genes identified as expressed in HK-2 renal tubule epithelial cells. We previously performed RNA-seq analysis of immortalized human proximal tubule epithelial cells (HK-2) (Brennan et al., PMID: 22266139). From these data, a total of 11,732 genes were robustly expressed in HK-2 cells. Here we investigated the tubule compartment-specific expression of these genes in 14 compartments of a micro-dissected rat renal tubule. Rat renal tubule data was downloaded from (https://hpcwebapps.cit.nih.gov/ESBL/Database/NephronRNAseq/index.html) Lee JW et al., JASN 2015. PMID: 25817355. Red = higher expression; Blue = lower expression. Terminology for nephron segments: S1, first segment of the proximal tubule; S2, second segment of the proximal tubule; S3, third segment of the proximal tubule; SDL, short descending limb of the loop of Henle; LDLOM, long descending limb of the loop of Henle in the outer medulla; LDLIM, long descending limb of the loop of Henle in the inner medulla; tAL, thin ascending limb of the loop of Henle; mTAL, medullary thick ascending limb of the loop of Henle; cTAL, cortical thick ascending limb of the loop of Henle; DCT, distal convoluted tubule; CNT, connecting tubule; CCD, cortical collecting duct; OMCD, outer medullary collecting duct; IMCD, inner medullary collecting duct.

Table S1. Differentially expressed genes between control and diabetic ApoE-/- mice. Log2 Fold- FDR (CORRECTED P- Log2 Fold- FDR (CORRECTED P- GENE ID change VALUE) GENE ID change VALUE) Eda2r 3.77 8.73E-65 Kif23 0.85 0.009579192 Cdkn1a 3.22 4.75E-54 Adamts14 0.82 0.009676948 Trp53cor1 3.25 1.63E-34 Serpine2 0.73 0.009843774 Gm45011 2.97 6.92E-30 Espnl 0.77 0.010012367 Psrc1 4.40 2.16E-26 Nat8 -0.71 0.010136542 Kcnip4 2.55 1.16E-25 Lrrc32 0.49 0.010142684 Dscaml1 2.96 1.16E-25 Cd247 0.84 0.010248419 4933406I18R Ano3 4.11 1.97E-22 ik 0.62 0.010332392 Mgmt 1.15 5.35E-17 Hmgcr -0.92 0.01036763 Fam212b 2.75 2.16E-15 Tnnc1 -1.45 0.010553111 4933427D06 Zmat3 0.94 4.23E-14 Rik 1.48 0.010554075 Trpm8 3.88 1.02E-13 Kcnip2 1.09 0.010564754 Sulf2 1.15 1.86E-13 Rhoq 0.39 0.01060559 Plcd4 1.46 5.28E-13 Gm16432 0.59 0.010622298 Dpp6 1.49 3.16E-12 Ctsk 0.75 0.010797885 Gtse1 2.11 1.70E-11 Fmo5 -0.66 0.010840349 Ugt1a10 4.26 1.74E-11 Dtx4 0.67 0.010987816 Trp53inp1 1.07 4.03E-11 Cbr1 1.20 0.011006467 Gm26542 1.18 4.89E-11 Slc8a3 1.26 0.011006467 Cldn1 1.12 1.58E-10 Gm10830 1.35 0.011066719 Plk2 1.04 1.58E-10 Ttpa 0.93 0.011309208 6030407O03 Rik 1.69 2.81E-10 Ube2e2 0.42 0.011322178 4833428L15 Rik 3.98 1.02E-09 Blm 0.73 0.011653609 Cyp2d12 -1.92 1.30E-09 Ccl6 1.06 0.011746526 Tnfaip8 -1.12 1.92E-09 Psat1 -0.72 0.01181329 Tll2 2.82 2.18E-09 Xbp1 -0.63 0.011909845 Alk 1.34 2.87E-09 Polq 0.84 0.012000339 D630023F18 Rik -1.74 3.37E-09 Plk3 1.15 0.012060378 Kynu 2.45 4.93E-09 Acta2 0.75 0.012162165 Gdf15 1.39 6.15E-09 Tox 0.72 0.012443309 Ddias 1.76 9.81E-09 Chrna4 -0.71 0.012443309 Gm13067 1.52 1.58E-08 Vwc2 2.24 0.012443309 Angptl7 -2.01 2.26E-08 Gm19418 1.08 0.012583916 Nudt19 -1.11 3.72E-08 Nabp1 0.48 0.012708693 Ccng1 0.85 3.72E-08 Ces2b -1.33 0.012710387 RP23- Phlda3 1.84 4.41E-08 403G9.6 -0.58 0.012866647 Aldh1a7 1.27 5.82E-08 Masp1 1.42 0.012866647 Ppp1r1c 3.03 5.82E-08 Iba57 -0.61 0.012908268 Gm10787 -1.61 9.37E-08 Egr1 1.05 0.013002775 Gm10801 2.84 1.44E-07 Pcdh9 1.00 0.013088521 Ptprt 2.02 1.44E-07 Art4 0.72 0.013434097 Gpc3 0.94 2.07E-07 Cyp2d9 -0.58 0.013721646 Aen 0.82 3.29E-07 Csrp1 0.47 0.013779774 Ccnd1 1.05 3.30E-07 Mmp14 0.64 0.013882712 Ngef -0.62 3.87E-07 Dnajb1 -0.46 0.013962789 Npr3 -0.96 3.97E-07 Col24a1 0.83 0.01405554 Gm6614 2.69 6.07E-07 Hsp90aa1 -0.75 0.014088302 Gjb1 -0.79 6.95E-07 Isoc2b -0.59 0.014412196 Fn1 1.03 6.95E-07 Tagln 0.71 0.014448187 Sntg1 1.76 6.95E-07 Ttk 1.34 0.014691235 1700024P16 Rik 1.77 7.69E-07 Gpc5 -1.10 0.015017502 Cpne4 -1.30 8.91E-07 Mrvi1 0.40 0.015095492 Ces1d -0.90 1.81E-06 Dclk3 -0.50 0.015189655 Gm12153 1.29 1.86E-06 Klhl9 -0.42 0.015298851 Ltc4s 1.32 2.55E-06 Hspe1 -0.67 0.015298851 Nat8f6 -1.01 3.14E-06 Ccnf 0.99 0.015298851 Zak 0.87 3.22E-06 Mctp2 0.67 0.015576738 Mab21l3 1.21 3.22E-06 Gm4593 0.86 0.015589538 Diaph3 1.16 3.72E-06 Svop 1.51 0.016125581 Gm9732 2.66 4.61E-06 Abhd3 -0.55 0.016238576 Gm44202 1.65 4.61E-06 Kif22 1.28 0.016238576 Slc19a2 0.70 6.58E-06 Gm13387 0.83 0.016238576 Ppp2r2c 1.83 6.99E-06 Rundc3a 0.82 0.016238576 Tmem43 0.79 7.00E-06 Chaf1b 1.18 0.016304122 Aldh1a1 1.69 7.66E-06 Gm12999 -1.25 0.01662482 Tnfrsf10b 1.08 8.71E-06 Spag6l 0.72 0.016674081 Cdh2 -0.77 9.52E-06 Mamld1 0.80 0.0168547 A930001C03 Rik 0.87 1.09E-05 Atf3 0.85 0.0168547 Gm37795 1.37 1.09E-05 Rimkla 0.88 0.0168547 9130019P16 Grem1 3.81 1.14E-05 Rik 1.03 0.016879702 Gm29282 1.76 1.18E-05 Tm4sf4 -1.29 0.016892269 Mki67 1.30 1.19E-05 Gckr 1.20 0.016973187 Clca3a1 1.89 1.48E-05 Gm11837 -1.09 0.017027586 Olfr1442 2.54 1.65E-05 Shh -1.26 0.017027586 Ckap2 1.84 1.67E-05 Asic2 1.29 0.017050281 Ephx1 1.20 1.70E-05 Wisp1 0.68 0.017050281 Hsph1 -0.96 1.91E-05 Nepn -0.86 0.017064629 Hspa1a -1.41 2.06E-05 Gm15563 -2.01 0.017167265 Anln 1.47 2.08E-05 Gpr135 1.00 0.017167265 Akr1c13 0.99 2.44E-05 Gm44626 -1.08 0.017167265 B3galt1 0.82 2.57E-05 Tnfsf13b 0.70 0.017272276 Zbtb40 -0.68 2.60E-05 Birc5 1.25 0.017289706 P2ry1 -0.87 3.56E-05 Nlgn1 0.89 0.017505002 G6pc -1.13 4.31E-05 Ankrd34b -1.49 0.017585986 Loxl4 1.32 4.44E-05 Rell1 0.45 0.017675365 Cxcl10 1.49 4.59E-05 Ahcy -0.48 0.017675365 9230114K14 Rik 0.57 4.80E-05 Gabrb3 -1.02 0.01771164 Cpe -0.97 5.18E-05 Entpd1 0.72 0.017859166 Ces2e 0.80 5.32E-05 Dpysl3 0.59 0.017975549 Snhg11 -0.61 5.51E-05 Gm16010 1.26 0.017975549 Fbn1 0.67 5.51E-05 Kcnmb2 0.75 0.018197911 Esco2 1.93 5.51E-05 G0s2 -0.66 0.018346224 Cpb2 2.10 5.59E-05 L3mbtl4 1.04 0.018474941 Lbp 1.16 6.23E-05 Dnaja1 -0.56 0.018513498 Osr2 -1.20 6.58E-05 Arhgef38 0.52 0.018712977 Sh3rf3 1.45 7.56E-05 Aspdh -0.87 0.01871427 Gm15441 -2.18 7.81E-05 Ldhd -0.76 0.01871427 Mlip 1.77 7.83E-05 Gm44829 0.96 0.018722012 Vmn2r1 1.97 7.83E-05 Gm15581 0.84 0.018904148 Antxr1 0.88 7.83E-05 Ces2c -0.75 0.018944215 Stc1 1.29 8.29E-05 Ccdc6 -0.48 0.019035014 Cyp2j8 1.14 8.42E-05 Stra6l 0.59 0.019125513 2310014F06 Synpo2 0.79 9.22E-05 Rik 0.72 0.01915912 Gabra3 0.78 9.22E-05 BC051142 0.96 0.019163403 4833411C07 Rik -1.83 9.46E-05 Rarres2 1.05 0.019167588 Car3 -1.97 9.66E-05 Adam22 0.44 0.019549955 C3 1.44 9.74E-05 Arhgef33 0.81 0.019549955 Gucy1a3 0.67 0.000103542 Hao2 0.63 0.019564117 2610027K06 Slc39a5 -1.05 0.000103542 Rik -0.59 0.019564117 A830018L16 Kcnab1 1.40 0.000105161 Rik 1.65 0.019564117 Arhgef4 0.97 0.000107839 Fam195a -0.59 0.019564117 Col14a1 0.72 0.000109055 Tmem50a -0.44 0.019564117 Kcnma1 0.82 0.000109088 Slc6a15 -0.53 0.019564117 1700027A15 Rik 1.83 0.000123863 Il20rb 0.82 0.019564117 C630028M0 4Rik 2.33 0.00012486 Gja5 0.73 0.019564117 Tcf24 -0.84 0.000134654 Gm906 -1.49 0.020080732 Cemip 1.62 0.000156583 Gm8439 1.64 0.020102085 Aldh1b1 1.41 0.000174496 Slc22a27 1.19 0.020235153 Snap91 1.43 0.000174496 Ms4a6c 0.79 0.020622041 Zwilch 1.06 0.000178174 Mfap2 1.13 0.020776688 Hspa1b -1.49 0.000180276 Nsun7 0.64 0.020926983 Brca1 1.09 0.000184119 Cd84 0.83 0.021183298 Iqgap3 1.39 0.000185756 Kntc1 0.98 0.021668322 Dlgap5 1.46 0.000185756 Fat1 0.42 0.02170867 Dll4 -0.91 0.000186624 Ace -0.55 0.022130938 Adamts5 0.60 0.000200843 Akr1d1 0.51 0.022130938 Gm11100 2.07 0.000204423 Rorc -0.49 0.022216895 1600010M0 7Rik -1.08 0.000221037 Vegfa -0.43 0.02245845 Asb11 1.49 0.000230907 Gabrr2 -0.92 0.02268808 Mis18bp1 1.40 0.000230907 Angptl2 0.43 0.022941247 Clspn 1.49 0.000251601 Col12a1 0.85 0.022941247 Tmem28 -1.06 0.000262189 Tnip3 1.02 0.023305612 Gm13412 -1.31 0.000262189 Tmem205 -0.51 0.023605316 Nusap1 1.02 0.000265928 Sla 0.73 0.023674524 Nefl 1.94 0.000276385 Slc38a3 0.88 0.023848864 Nkain1 -0.84 0.000284846 Zfp958 0.41 0.02387842 Depdc1b -0.58 0.000304407 Cyp51 -0.50 0.02387842 Arhgap11a 1.12 0.000309154 Cyp4b1 -1.01 0.023911415 Ubiad1 -0.60 0.000311596 Apol9b 1.10 0.023911415 Svep1 0.51 0.000317005 Epha7 -0.85 0.02398354 2810433D01 Fam198b 0.78 0.000318875 Rik 1.14 0.02398354 Cdk1 1.30 0.000335156 Col8a1 -0.94 0.02398354 Olfr1443 1.74 0.000344768 Rad54b 1.00 0.02398354 Car4 -0.80 0.000345106 Nr4a1 1.11 0.02398354 4732471J01 Rik -0.57 0.000348188 Npl 0.82 0.024041142 C030034L19 Ackr3 -0.77 0.000352541 Rik 1.26 0.024041142 Samd5 1.30 0.00035903 Shcbp1 0.97 0.024041142 Nid1 0.52 0.00035903 Crtam 2.15 0.024041142 Fbln5 0.58 0.000398897 Fcamr -1.14 0.024041142 Nat8f1 -0.93 0.000399305 Acy3 -0.94 0.024041142 Esm1 -1.21 0.000450988 Dhrs4 -0.59 0.024181005 Nebl 0.62 0.000464149 Plekhb1 -0.55 0.024653927 Gas2l3 1.01 0.000464149 Cmya5 0.61 0.024653927 Paqr7 -0.97 0.000470847 C3ar1 0.79 0.024698889 Pole 1.18 0.000475154 D2hgdh -0.42 0.024698889 Tex15 1.33 0.000477106 Trpv6 0.91 0.024903267 Cfap44 1.16 0.000492976 Tet2 0.45 0.024903267 Apoh -1.30 0.000492976 Ccl5 1.13 0.024903267 Gsta2 1.01 0.000492976 Gmpr -0.41 0.024950708 E230016K23 Rik 1.05 0.000527561 Rad51b 0.72 0.025158381 Sdk1 0.76 0.000543535 Stra6 1.25 0.02525358 Mmp2 1.29 0.000557573 Gm3294 1.29 0.02536072 Mgp 0.89 0.000572491 Kcng3 1.28 0.025624924 Tspan2 0.87 0.000572491 Gm44127 2.30 0.025750159 Mpped1 1.34 0.00058469 Exoc4 0.49 0.025968133 Coq10b -0.54 0.000594251 Gm15983 0.76 0.026369828 Slc25a42 -0.66 0.000624609 Cd4 0.97 0.026395722 L3mbtl1 1.58 0.000643541 Pappa 0.71 0.026404126 Cox6a2 -2.00 0.000644584 Aspg -0.78 0.026698243 Bgn 0.60 0.000699478 Manf -0.75 0.027002345 Neat1 0.98 0.000701642 Kif1a 1.16 0.027160412 Neil3 1.56 0.000723987 Calb1 0.52 0.027160412 Stc2 1.01 0.000857293 Hivep3 0.46 0.027160412 Uhrf1 1.19 0.000858778 Fkbp4 -0.63 0.027160412 Pigz 1.43 0.000877231 Lama2 0.47 0.027160412 Mdm2 0.47 0.00099063 Sobp 0.71 0.02729716 4930578G10 Gm5717 1.02 0.00099063 Rik 1.50 0.027913396 Poln 1.53 0.00099063 Gm43016 1.09 0.027913396 A930033H14 Rik -0.88 0.00099063 Slc7a12 1.85 0.02803113 Casc5 1.10 0.00099063 Lgals3bp 0.72 0.028090663 Akr1c20 1.91 0.000999734 Gm13111 -0.61 0.028090663 Gpnmb 2.50 0.00100703 Kcnab2 -0.64 0.028326102 F2r 0.74 0.001033634 Slc16a14 -0.92 0.028326102 Vcam1 0.79 0.001033634 Parpbp 0.88 0.028326102 Adamtsl3 1.01 0.001123391 Kcnt2 0.57 0.028568858 Gm3448 0.94 0.001123391 Pir 0.70 0.028790527 Tmtc4 -0.71 0.001147034 Rab31 0.54 0.028964715 Tmem132b 1.79 0.001147034 Prima1 -0.67 0.028969828 Sparcl1 0.87 0.001164123 Gm16505 -1.33 0.028969828 A330033J07 Rik 1.41 0.001192759 Smim22 -1.00 0.029457905 Ms4a7 0.91 0.001214604 Slc13a3 -0.59 0.029805665 Slc16a10 -0.66 0.001361023 Fcgr2b -0.54 0.029805665 Hmcn1 0.68 0.001393465 Lonrf1 -0.71 0.02990429 Trpm3 0.85 0.001393465 Slc34a3 -0.84 0.02990429 Melk 1.31 0.001393465 Birc3 0.48 0.03003825 Dgkb -0.61 0.001393465 Sap30 -0.73 0.03003825 Exo1 1.69 0.001398249 Hpgds 0.80 0.03014368 Cp 1.09 0.001400168 Fads2 -0.42 0.030150818 Ftcd 0.74 0.001413579 Nrap 0.85 0.030151069 Pappa2 -1.96 0.001438359 Gm38048 1.02 0.030271805 Il33 0.83 0.001469406 Card14 0.65 0.030271805 Smad7 -0.64 0.001500351 Plxna2 0.39 0.030271805 Grm8 1.30 0.001509827 Aldh3b3 -0.95 0.030271805 Abca1 0.66 0.001561889 Aadat -0.54 0.030311443 Prc1 1.03 0.001567868 Lockd 0.84 0.030311443 Slitrk4 2.61 0.001567868 Slc17a1 -0.52 0.030311443 Gm1604b 0.91 0.001620691 Fos 1.28 0.030311443 Ahsa2 -0.65 0.001635698 Srgap1 0.43 0.030486144 Gm34240 1.59 0.001635698 Serping1 0.63 0.030977724 Mt1 1.11 0.001644429 Gm44174 1.06 0.030990933 Ccdc18 1.16 0.00167064 Ahsa1 -0.52 0.030990933 RP24- Cacna1e 0.88 0.00169607 420C18.2 -1.50 0.030990933 Rasa3 0.55 0.001711702 Ces1f -0.72 0.030990933 Spock1 1.96 0.00177848 Gm10271 -0.74 0.03159661 Stil 1.19 0.00177848 Gda -0.45 0.03159661 Pcdh11x -1.49 0.001804795 Lyz2 0.69 0.03159661 Rrm2 0.94 0.001823116 Zfp385a 0.59 0.03172998 Kif4 1.08 0.001837703 Wdr27 0.67 0.032079904 Zfp423 0.68 0.001842448 Fbn2 1.22 0.032205903 Acaa1b -0.76 0.001848029 Irf7 0.70 0.032685999 Cd86 0.82 0.001899982 Ggct -0.60 0.03292138 Lin7a -0.67 0.002016067 Plch1 0.56 0.033011608 C1qtnf3 -0.88 0.002016067 Tmem237 -0.64 0.033022533 Ttr -1.04 0.002023144 Gm10388 1.37 0.033022533 A2m -2.15 0.002043764 Cmtm6 -0.65 0.033022533 Pate2 1.17 0.002051858 Platr25 0.80 0.033057218 Themis 1.04 0.002080101 Stk35 -0.41 0.033242429 2810407A14 Rik 1.12 0.002177895 Slc16a12 -0.44 0.033250425 St18 1.55 0.002210048 Ncapg 1.11 0.033553422 4932411K12 Rik 1.21 0.002374687 Rasl10b 1.15 0.033553422 Tpx2 0.99 0.002381173 Hspa8 -0.65 0.033553422 Hsd17b2 -0.64 0.002532463 Amacr -0.84 0.033553422 Odc1 -1.17 0.002532463 Fam129a 0.55 0.033646919 8430419K02 Scg5 0.94 0.002599677 Rik 1.35 0.033646919 Bdkrb2 1.20 0.002599677 Aspm 0.77 0.033646919 Crb1 -1.32 0.002627013 Acad10 -0.41 0.033646919 Gm43948 1.79 0.002654872 Mettl7b -0.54 0.033646919 Dtl 1.26 0.002654872 Echdc2 -0.55 0.033983605 Xlr3a -1.77 0.002654872 Alox5 1.11 0.034123737 Pros1 0.58 0.00267056 Ebp -0.40 0.034251399 Atp2b4 0.50 0.002729759 Rbm3 0.45 0.034558151 Myl9 0.58 0.002790733 Amdhd1 1.05 0.034660217 Stip1 -0.62 0.002971899 Bard1 0.61 0.034781805 Zdhhc19 1.75 0.002974115 Gm28802 1.42 0.034781805 Rbm11 1.23 0.003081189 S100a10 0.43 0.034911821 Dcn 0.84 0.003081189 Fasn -0.48 0.034973702 Dnaja4 -0.54 0.003092947 Sdf2l1 -0.89 0.035105961 Agt 0.81 0.003096125 Kif11 0.83 0.035207811 Miox -0.83 0.003105081 Josd2 -0.81 0.03540355 A330093E20 C1s1 0.69 0.003114916 Rik 1.26 0.03540355 F5 -1.49 0.003123712 Haao -0.56 0.035406525 Gabbr2 1.04 0.003204399 Hspa4l -0.41 0.035447112 Cyp1b1 0.74 0.00322941 Garnl3 0.83 0.035730371 Nqo1 1.12 0.003235666 Hells 0.62 0.036051544 Abca14 1.08 0.00325968 Zfp706 -0.38 0.036147321 Dscam 1.76 0.003318636 Pcyt2 -0.37 0.036323018 Nrg1 0.61 0.00336306 Kif18b 1.25 0.036324642 Runx2 0.60 0.003416652 Mgat3 -0.44 0.036490376 Rxrg 1.54 0.003452638 Thsd1 0.56 0.036490376 Cdh11 0.62 0.003481264 Cpox -0.51 0.036653391 Ncapg2 0.75 0.003568569 Dnajb2 -0.42 0.036760048 Gm11766 -1.27 0.003568569 Fanci 0.94 0.036847148 Ugt2b5 1.06 0.003568569 Gm14232 1.05 0.036847148 4930533I22 Rik -0.67 0.003573506 Cpt2 -0.41 0.036847148 Ighg2b 1.78 0.00372872 Prune2 1.22 0.037013926 Slc9a8 -0.61 0.003778066 Ezh2 0.43 0.037180113 Golm1 0.89 0.003792713 Wfdc15b -0.77 0.037212028 Pth2r 1.11 0.003820403 Hist1h3c 1.08 0.037212028 Polk 0.44 0.003860633 Capsl 1.17 0.037212028 Arnt2 0.53 0.003879127 Cbr3 1.31 0.037212028 Ank1 1.00 0.00395734 Grb7 -0.48 0.037401673 Slc41a3 0.67 0.00395734 Zbed3 -0.43 0.037401673 Gm45051 -1.40 0.004038009 Ctss 0.49 0.037401673 Egfem1 0.83 0.004038009 Galnt11 -0.47 0.037665631 Naip1 1.87 0.004043629 Hhat 0.40 0.037741723 Nap1l5 -1.14 0.004043629 Pde10a 0.65 0.038099067 Palm3 0.71 0.004065742 Gm14963 -0.76 0.038138357 Col27a1 -0.94 0.004080484 Iqcc -0.54 0.038138357 Fetub 1.11 0.004080484 Gpr173 0.85 0.038138357 Mcm5 0.82 0.004121968 Cbs -0.40 0.038170561 Kif15 1.11 0.004173332 Msh4 0.91 0.038170561 Spp1 0.99 0.004231284 Etv1 -0.97 0.038189078 Ung 1.32 0.004237784 Cpt1c 0.83 0.038387017 Efcab11 0.86 0.004315425 Kcnh7 -1.91 0.03840228 Epha6 0.95 0.004394363 St8sia6 -0.37 0.038415909 9130409J20 Mttp -0.61 0.004460026 Rik -3.12 0.038456009 9930014A18 Gm26672 -1.23 0.004662414 Rik 0.67 0.038456009 Wdhd1 0.75 0.004765688 Chaf1a 0.64 0.038703022 1500017E21 Inmt -1.19 0.004879528 Rik 1.29 0.038715575 Dpf3 -0.48 0.004906669 Lif 0.96 0.039174148 Gm7205 0.94 0.00515389 Gm42636 1.11 0.039396669 Extl1 1.27 0.00515389 Tchhl1 0.95 0.039560702 Rgs5 0.61 0.00515389 Chrdl2 1.73 0.039560702 Slitrk6 -0.97 0.00517332 Creld2 -0.76 0.039560702 Chordc1 -0.48 0.005227557 Slc25a25 -0.66 0.040067622 Efcab8 1.41 0.005244149 Gm13660 1.09 0.040067622 Ccdc148 0.49 0.005334889 Zfp462 0.35 0.040078084 Pde6h 0.80 0.005373115 Cyp2j11 -0.37 0.040078084 A430093F15 Rik 1.41 0.005591928 C7 1.07 0.040155285 Epha3 0.84 0.005637197 Gbp8 0.68 0.040222844 Akr1c12 0.87 0.005637329 P2rx7 0.66 0.041585874 Bhmt 1.11 0.005654491 Pi15 0.61 0.041868071 6030443J06 Rik 0.51 0.005659182 Sparc 0.45 0.04230449 Vegfd 0.65 0.005659182 Hsp90ab1 -0.62 0.042446532 RP24- 335D17.3 -1.29 0.005673471 Hfe 0.47 0.042446532 Serpinf2 -0.82 0.005732809 Cbfa2t3 -0.45 0.043113383 Slc22a3 1.29 0.005732809 Brca2 0.55 0.043176121 Abcb1a 0.87 0.005732809 Slc7a13 -0.72 0.043479187 Ndnf 1.81 0.005736337 Hmmr 0.98 0.043547863 Cby3 1.81 0.005828929 Zbtb7a -0.43 0.043547863 Lpo 1.89 0.005937133 Zgrf1 0.63 0.043547863 Aldh1a2 0.94 0.006062034 Ddit4 1.18 0.043547863 Mt2 1.24 0.006237894 Pabpc1l 1.69 0.043671738 Clic6 1.98 0.006250089 Slc5a10 0.42 0.043778655 Fancd2 1.00 0.00630813 Lad1 -0.33 0.043888974 Mpeg1 0.62 0.006459064 Gm17597 -1.04 0.043955773 Veph1 -0.50 0.006755023 Nxpe4 0.63 0.04410416 Papln 0.77 0.006840456 Gucy1a2 0.39 0.04410416 Prdm1 -0.82 0.006840456 Acss2 -0.44 0.04411085 Egflam 0.50 0.006853085 Eps8l1 -0.58 0.044230408 Scara3 1.84 0.006994451 Pard3bos3 -1.26 0.044248429 Btnl9 -0.78 0.007005095 Spp2 -0.64 0.04457674 Lsmem1 1.03 0.00707001 Scrn2 -0.67 0.045363229 Ddo -0.40 0.007081921 Vwa2 -0.46 0.045760312 Slc17a4 -1.12 0.007081921 Txlng -0.33 0.045806295 Atp8b5 0.89 0.007081921 Celsr2 -0.36 0.045837082 Neurog2 -1.15 0.007176829 Mgst1 0.49 0.045912116 Ptprq 1.47 0.007231643 Syt2 1.05 0.045915511 Mybl1 0.83 0.007268832 Mpzl2 0.62 0.045965473 Snhg15 0.93 0.007297226 Pdzk1 -0.55 0.045965473 Oasl1 0.92 0.007297226 Cdkl1 -0.48 0.046124427 Fam149a -0.59 0.007328242 Myrfl 0.88 0.046390059 Nectin1 0.53 0.007364756 Irak3 0.73 0.046390059 D630003M2 Acad12 -0.42 0.007390619 1Rik -0.72 0.046390059 A330015K06 Rik 1.20 0.007390619 Ccdc180 -1.11 0.046390059 1810064F22 Rik 1.25 0.00742241 Chst7 -0.78 0.046398145 Gm1604a 1.08 0.007542888 Fcgbp -2.12 0.046398145 Cys1 -0.59 0.007574571 Procr 1.02 0.046662811 Dnajc12 -0.70 0.007701768 Rnf145 -0.35 0.046700417 Gria3 0.60 0.007764025 Gm43568 -0.68 0.046972621 Glyctk -0.62 0.007764025 Spats2l -0.64 0.047350128 Ak4 -0.67 0.007844291 Gm6999 0.57 0.047350128 Clec12a 0.87 0.00788046 Acat1 -0.48 0.047350128 2010300C02 Rik -0.82 0.00788046 Gm15264 0.56 0.047418026 Nrep -0.82 0.007899711 Myof 0.75 0.047418026 Aldh1a3 -3.40 0.008037724 Akr1b7 0.92 0.047566544 Wnt11 -2.65 0.008046393 Impg2 0.52 0.047747713 Slc15a1 1.02 0.00817401 Tgfbi 0.51 0.047756606 Arhgap27 -0.42 0.008283679 Klf6 0.37 0.047888831 Gm45083 0.63 0.008453823 Tmem150a -0.55 0.047888831 Xkr4 0.88 0.00849699 P4ha1 -0.40 0.047976242 Tcf23 2.03 0.008745751 Ccnb1 1.03 0.048066198 Trim9 2.05 0.008782161 Msi1 0.95 0.048066198 Ltbp2 1.87 0.008873874 Gcnt3 -2.96 0.048066198 Vwa3a 0.88 0.008873874 Nek6 0.37 0.048066198 Igfbp4 -0.80 0.008874681 Knstrn 0.71 0.048614289 Gm20755 1.10 0.009074906 Tubb6 0.80 0.048614289 Adh6b 2.64 0.009100906 Fam169b -0.36 0.048853805 Acsbg1 1.22 0.009104592 Cfh 0.49 0.048971437 Slc16a13 -0.74 0.009104592 Tlr13 0.85 0.0490811 Ogn 0.71 0.009161829 Srpx 0.84 0.049755752 C330027C09 Rik 0.77 0.009381493 Rnf183 -0.63 0.04998003 Unc13c -1.09 0.009392039

Table S2. Upstream regulator analysis: Control versus diabetic ApoE-/- mice. Upstream Regulator Predicted Activation State Activation z-score p-value of overlap TRIM24 Inhibited -3.317 0.00000441 NEUROG1 Inhibited -3.162 0.00000861 SPARC Inhibited -3.162 0.000752 Irgm1 Inhibited -3.148 0.000000342 IRF4 Inhibited -2.946 0.00054 ATP7B Inhibited -2.828 0.00000143 KDM5B Inhibited -2.651 0.00203 HSF1 Inhibited -2.46 4.95E-11 GLIS2 Inhibited -2.449 0.00000381 miR-34a-5p Inhibited -2.443 0.000564 Inhibited -2.388 0.000165 AURK Inhibited -2.345 0.00000895 ANLN Inhibited -2.333 0.00000895 CBX5 Inhibited -2.333 0.00156 TAB1 Inhibited -2.236 0.000367 BNIP3L Inhibited -2.219 0.0191 ABCB4 Inhibited -2.216 0.00119 ZFP36 Inhibited -2.213 0.000564 SCAP Inhibited -2.183 0.0151 RB1 Inhibited -2.138 0.272 CD38 Inhibited -2.111 0.00383 PPARG Inhibited -2.044 0.000000506 SAV1 Inhibited -2 0.0000237 MST1 Inhibited -2 0.0000813 STAR Inhibited -2 0.000298 STK3 Inhibited -2 0.00042 TSC2 Inhibited -2 0.0117 LRP1 Inhibited -2 0.0122 ACKR2 Inhibited -2 0.0223 PRNP Inhibited -2 0.0513 MAPK14 Activated 2.04 0.00215 IL17A Activated 2.06 0.0673 ERBB2 Activated 2.064 4.91E-14 FGFR1 Activated 2.091 0.0514 FOXM1 Activated 2.094 0.0000772 IFNG Activated 2.097 0.000033 PRKCD Activated 2.131 0.00000726 Vegf Activated 2.138 0.000596 TLR9 Activated 2.141 0.00778 TAL1 Activated 2.145 0.00278 IFNB1 Activated 2.151 0.000157 SRF Activated 2.158 0.00111 VEGFA Activated 2.162 0.000205 F2 Activated 2.177 0.000565 HRAS Activated 2.19 0.000124 FOXO3 Activated 2.195 0.000051 TREM1 Activated 2.197 0.000579 KITLG Activated 2.197 0.0151 Activated 2.2 0.0016 MAP2K4 Activated 2.213 0.0014 TLR2 Activated 2.23 0.309 NFATC2 Activated 2.236 0.0126 IL12B Activated 2.236 0.0164 RELA Activated 2.248 0.0000999 EZH2 Activated 2.263 0.0000672 mir-223 Activated 2.331 0.000129 RETNLB Activated 2.345 0.000301 LCN2 Activated 2.353 0.00264 NR1I3 Activated 2.371 0.0000567 CREB1 Activated 2.375 0.00000291 AKT1 Activated 2.376 0.0000568 IFNAR1 Activated 2.378 0.00501 CYP1A1 Activated 2.4 0.00591 ERK Activated 2.412 0.000472 Akt Activated 2.415 0.000326 ELAVL1 Activated 2.433 0.0108 TNFRSF1A Activated 2.439 0.0000321 HTT Activated 2.449 1.04E-08 NQO1 Activated 2.449 0.000482 TMEM173 Activated 2.449 0.00131 HIPK2 Activated 2.449 0.00741 CCND1 Activated 2.466 4.23E-11 CHUK Activated 2.535 0.0000024 IKBKB Activated 2.548 1.1E-09 Ifnar Activated 2.592 0.0122 CREBBP Activated 2.599 0.0292 Jnk Activated 2.613 0.00000119 SMARCA4 Activated 2.64 0.000997 NEDD9 Activated 2.646 0.0000707 ERK1/2 Activated 2.765 0.0000672 PDGF BB Activated 2.777 0.000151 Cg Activated 2.823 1E-12 PTGER2 Activated 2.84 1.31E-08 NFkB (complex) Activated 2.843 0.000311 TICAM1 Activated 2.883 0.0107 RIPK2 Activated 2.918 0.000139 MYD88 Activated 2.938 0.0000623 TGFB1 Activated 2.957 2.53E-11 TP53 Activated 3.005 1.6E-21 FOXO1 Activated 3.102 0.000000193 IKBKG Activated 3.182 0.0000102 TLR3 Activated 3.201 0.00235 P38 MAPK Activated 3.283 0.00000115 RABL6 Activated 3.317 0.00000262 TNF Activated 3.377 2.47E-09 CSF2 Activated 4.176 1.29E-11

-/- Table S3. Upstream regulator analysis: Diabetic versus Diabetic + LXA4 or Benzo-LXA4 treated ApoE mice. Upstream Predicted Activation z- p-value of Regulator Molecule Type Activation State score overlap PDGF BB complex Inhibited -3.213 0.00000641 SREBF1 transcription regulator Inhibited -2.795 0.00199 RABL6 other Inhibited -2.449 0.0409 PTPN1 phosphatase Inhibited -2.425 0.00692 C3 peptidase Inhibited -2.4 0.00429 Growth hormone group Inhibited -2.345 0.00025 NCOA1 transcription regulator Inhibited -2.236 0.144 PI3K (family) group Inhibited -2.225 0.00584 -dependent nuclear NR1I2 receptor Inhibited -2.224 0.398 PLIN5 other Inhibited -2.219 0.00417 let-7 microrna Inhibited -2.2 0.0356 ligand-dependent nuclear AR receptor Inhibited -2.171 0.207 ligand-dependent nuclear PGR receptor Inhibited -2.13 0.000223 GMNN transcription regulator Inhibited -2.121 0.0127 PTEN phosphatase Inhibited -2.09 0.242 TNF cytokine Inhibited -2.09 0.0000856 IL27 cytokine Inhibited -2.082 0.0034 TREM1 transmembrane receptor Inhibited -2.07 0.135 ligand-dependent nuclear AHR receptor Inhibited -2.044 0.000000756 HAND1 transcription regulator Inhibited -2 0.000851 ATP7B transporter Inhibited -2 0.0172 miR-182-5p mature microrna Inhibited -2 0.0314 TNFRSF1B transmembrane receptor Inhibited -2 0.0977 APC enzyme Inhibited -2 0.145 UPF2 other Inhibited -2 0.0395 BMP15 growth factor Activated 2 0.000888 KDM1A enzyme Activated 2 0.0754 HDAC1 transcription regulator Activated 2.121 0.0152 FADD other Activated 2.219 0.15 BACH2 transcription regulator Activated 2.236 0.0253 H2AFY other Activated 2.236 0.00645 transcription regulator Activated 2.299 0.0468 FIGLA transcription regulator Activated 2.387 0.0233 ligand-dependent nuclear NR3C1 receptor Activated 2.401 0.0809 ligand-dependent nuclear PPARA receptor Activated 2.581 0.000000039 RICTOR other Activated 3.308 0.00678

Table S4. Differentially expressed genes: Diabetic -/- versus Diabetic + LXA4 treated ApoE mice. FDR (CORRECTED P- Gene ID logFC VALUE) Egr1 -1.43 2.06E-07 1600010M07Rik 1.24 0.004551304 Rorc 1.04 0.005418383 Jchain -1.48 0.005443802 Gm15441 1.47 0.005443802 Lamb3 0.93 0.006032177 Fcnaos 1.11 0.006357033 Gm45064 -1.47 0.007896206 Msmo1 -0.75 0.008307286 Cyp2c69 -1.61 0.00904752 Iglc1 -2.51 0.010555067 Insig1 -0.79 0.015245182 Igfbp1 -1.19 0.015245182 Lrat -1.24 0.020743571 Ngef 0.57 0.020743571 Tfrc -0.73 0.027328174 Aldh1a3 4.27 0.035119141 Adamtsl3 1.10 0.040081492 Per2 1.11 0.040081492 Lonrf3 0.94 0.049713619

Table S5. Differentially expressed genes: Diabetic versus -/- Diabetic + Benzo-LXA4 treated ApoE mice. GeneID logFC FDR (CORRECTED P-VALUE) Capn11 2.86 5.79E-08 Socs2 0.90 5.79E-08 Egr1 0.93 1.20E-05 Hbb-bs 1.21 0.000125237 Hba-a2 0.98 0.000237253 Glt1d1 -0.71 0.000260207 Ngef -0.47 0.000260207 Prr5 0.54 0.000299969 8430408G22Rik -1.18 0.000340402 Pak7 2.07 0.000373996 Hba-a1 0.91 0.001281152 Dscaml1 -1.01 0.001550101 Cfd 5.19 0.001877703 Atp2b2 -0.57 0.002746252 Plau 0.60 0.003776998 Kcnma1 0.77 0.008654365 Gm4450 0.52 0.00994191 Gm16010 1.49 0.011420084 Nat8f6 -0.87 0.012461811 Angptl7 -1.05 0.01523872 Slc7a12 2.22 0.01523872 Igfals 0.78 0.01523872 G6pc -0.47 0.01523872 Erdr1 -2.94 0.01526526 Lamb3 -0.62 0.020141288 Gm13052 -0.66 0.020141288 Zbtb40 -0.39 0.020798055 Insrr -0.62 0.021177013 Csgalnact1 0.39 0.021332777 D630039A03Rik 0.63 0.022088759 Ucp1 4.59 0.022088759 Tfr2 -1.51 0.023870615 Halr1 0.82 0.025706594 Nr4a1 1.16 0.025706594 Cish 1.00 0.027261422 Alk 0.66 0.031167045 Gm10787 -0.92 0.032380875 Retn 4.21 0.032789954 Gm17189 -0.72 0.033243619 Tmem37 0.89 0.034670499 Pitpnm2 -0.35 0.035585409 Gpc3 0.55 0.035585409 Adamtsl3 -0.98 0.036717043 Kyat1 -0.34 0.036955478 Ybx2 -0.43 0.039671637 Ncor2 -0.36 0.039671637 Aim1 -0.32 0.039671637 Slc7a7 0.50 0.039671637 Hspa1a -0.80 0.039767456 Slc15a4 -0.32 0.045446994 Tspan18 -0.42 0.049402702

Table S6. TFBS promoter analysis of differentially expressed genes from ApoE-/- RNA seq experiment Control versus diabetic diabetic ApoE-/- VS diabetic diabetic ApoE-/- VS diabetic ApoE-/- mice. ApoE-/- + LXA4 ApoE-/- + Benzo-LXA4 TF Z-Score TF Z-Score TF Z-Score Families (promoters) Families (promoters) Families (promoters) V$ZF5F 18.42 V$ZF5F 14.35 V$ZF02 21.04 V$E2FF 16.33 V$E2FF 8.11 V$EGRF 19.43 V$ZF02 13.38 V$NRF1 7.83 V$BEDF 16.07 V$NRF1 13.16 V$ZF02 7.63 V$PLAG 15.96 V$EGRF 12.74 V$EGRF 6.84 V$SP1F 14.91 V$GABF 11.71 V$HNFP 5.88 V$KLFS 14.91 V$BEDF 11.71 V$BEDF 5.76 V$ZTRE 13.92 V$SP1F 11.07 V$GCF2 5.43 V$GCF2 13.43 V$ZTRE 10.76 V$SP1F 5.19 V$MAZF 12.81 V$CTCF 10.31 V$CDEF 5.04 V$CTCF 12.19 V$MAZF 9.85 V$PLAG 4.72 O$XCPE 12.11 V$KLFS 9.16 V$EBOX 4.72 V$GLIF 11.68 V$PLAG 8.87 V$MAZF 4.52 V$E2FF 10.34 O$XCPE 8.45 V$NDPK 4.31 V$AP2F 10.08 O$MTEN 8.43 V$OAZF 4.3 V$ZF5F 10.05 V$CDEF 8.3 V$HESF 4.27 V$NDPK 9.98 V$NDPK 7.84 V$AP2F 4.21 V$NOLF 7.19 V$HDBP 7.8 V$GLIF 4.21 V$NFKB 7.11 V$GCF2 7.03 V$AHRR 4.1 V$STAF 6.99 V$HNFP 6.72 V$CTCF 3.91 V$ZF07 6.75 V$OAZF 6.26 V$ZTRE 3.87 V$RXRF 6.66 O$TF2B 6.24 V$BNCF 3.67 O$MTEN 6.63 V$GLIF 6.22 V$ZFXY 3.64 V$MZF1 6.63 V$ZF15 5.87 O$MTEN 3.59 V$RREB 6.47 V$AHRR 5.66 V$KLFS 3.53 V$HDBP 6.23 V$EBOX 5.33 V$ZF07 3.46 V$HESF 6.15 V$NFKB 5.06 V$CHRE 3.37 V$GCMF 5.98 V$HESF 5 V$NF1F 3.23 V$INSM 5.95 V$MZF1 4.94 V$NRSF 3.21 V$NRF1 5.86 V$ZF57 4.68 O$XCPE 3.16 V$SPZ1 5.83 V$ZF07 4.52 V$ZF57 3.13 V$SAL2 5.77 V$PAX9 4.47 V$SMAD 3.01 V$NRSF 5.2 V$NOLF 4.33 V$HAND 2.97 V$SMAD 4.95 V$MTF1 4.32 V$GABF 2.8 V$PEG3 4.88 V$SAL2 4.23 V$MOKF 2.76 V$PURA 4.54 V$AP2F 4.14 V$ZF11 2.72 V$ZF57 4.49 V$NRSF 4.05 V$NOLF 2.71 V$BNCF 4.32 V$WHNF 4.02 V$NFKB 2.68 V$EBOX 4.26 V$PRDM 3.77 V$MTF1 2.38 V$PAX5 4.15 V$ZICF 3.51 V$SPZ1 2.34 V$NF1F 4.04 V$HIFF 3.44 V$IKRS 2.26 V$CHRE 3.97 V$CHRE 3.32 V$ZICF 2.25 V$ZF11 3.84 V$MIZ1 3.04 V$THAP 2.19 V$ZFXY 3.66 V$PERO 2.94 V$ZF15 2.18 V$NR2F 3.57 V$NF1F 2.94 V$MIZ1 2.08 V$AHRR 3.53 V$GCMF 2.93 V$RXRF 2.08 V$OAZF 3.47 V$PURA 2.82 V$MYOD 2.03 V$PRDM 3.46 V$HEAT 2.8 V$LTFM 1.99 V$ZICF 3.44 V$PAX5 2.75 V$HDBP 1.97 V$ESRR 3.41 V$STAF 2.62 V$CREB 1.97 V$CDEF 3.3 V$CARE 2.59 V$AP4R 1.88 O$TF2B 3 V$INSM 2.46 V$PAX9 1.75 V$MIZ1 3 V$GTBX 2.44 V$DICE 1.74 V$HNFP 2.83 V$AP4R 2.39 V$HIFF 1.71 V$MYOD 2.6 V$ZBED 2.21 V$ZF04 1.69 V$PAX9 2.59 V$ZFHX 2.13 V$RREB 1.68 V$DMTF 2.47 V$DEAF 2.11 V$STAF 1.57 V$EREF 2.45 V$ETSF 2.04 O$TF2B 1.56 V$SRFF 2.43 V$MYBL 2 V$CSEN 1.5 V$ZF35 2.42 V$ZF35 2 V$SAL2 1.47 V$SF1F 2.36 V$SREB 2 V$INSM 1.46 V$ZF04 2.27 V$MYOD 1.93 V$TEAF 1.46 V$YBXF 2.27 V$HZIP 1.87 V$ZF01 1.38 V$HICF 2.26 V$HASF 1.86 V$CARE 1.18 V$RBPF 2.26 V$FXRE 1.71 V$RBPF 1.09 V$PERO 2.24 V$PRDF 1.7 V$GRHL 1.01 V$HIFF 2.19 V$NGRE 1.69 V$MEF3 0.99 V$NACA 2.16 V$DMTF 1.63 V$EREF 0.97 V$TAIP 1.95 V$RREB 1.62 V$PRDM 0.96 V$HASF 1.88 V$PROX 1.4 V$MZF1 0.93 V$MOKF 1.88 V$SNAI 1.39 V$NEUR 0.9 V$PTF1 1.86 V$XBBF 1.35 V$CP2F 0.87 V$RORA 1.84 V$ESRR 1.32 V$PROX 0.79 V$HAND 1.74 V$AP1R 1.31 V$SNAI 0.75 V$LTFM 1.68 V$CP2F 1.19 V$NGRE 0.69 V$DEAF 1.63 V$RBPF 1.18 V$PAX5 0.69 V$WHNF 1.61 V$P53F 1.17 V$TALE 0.69 V$CARE 1.59 V$BARB 1.15 V$DMTF 0.6 V$GTBX 1.58 V$SMAD 1.13 V$SRFF 0.57 V$NGRE 1.49 V$DICE 1.09 V$GCMF 0.56 V$SREB 1.45 V$ZF11 1.04 V$E4FF 0.56 V$ZF10 1.43 V$NACA 0.99 V$NACA 0.52 V$CP2F 1.4 O$INRE 0.98 V$MYRF 0.5 V$RBP2 1.36 V$NR2F 0.91 V$RBP2 0.49 V$P53F 1.35 V$YBXF 0.91 V$ZF35 0.46 V$CSEN 1.29 O$TF2D 0.91 V$ZF06 0.42 V$AP1R 1.27 V$SPZ1 0.89 V$NFAT 0.4 V$NEUR 1.18 V$CHOP 0.89 V$ESRR 0.33 V$SNAI 1.17 V$RXRF 0.89 V$HICF 0.29 V$XBBF 1.16 V$RBP2 0.83 V$SF1F 0.28 V$ZF01 1.15 V$IRFF 0.83 V$NKX1 0.27 V$IKRS 1.13 V$TALE 0.75 V$ZBED 0.23 V$MYRF 1.08 V$MOKF 0.72 V$YBXF 0.21 V$CAAT 1.05 V$PAX1 0.71 V$SREB 0.19 V$DICE 1.02 V$PAX3 0.62 V$ZFHX 0.19 O$TELO 1.01 V$NBRE 0.61 V$BRAC 0.18 V$NBRE 1 V$PAX6 0.58 V$P53F 0.17 V$GREF 0.97 V$GRHL 0.57 V$PPAR 0.13 V$AP4R 0.92 V$AP1F 0.54 O$TF2D 0.11 V$MTF1 0.84 V$NFAT 0.49 V$PURA 0.06 V$PAX3 0.76 V$GCNR 0.47 V$AP1R 0.01 V$PAX6 0.64 V$SF1F 0.45 V$ZF03 0 V$BRAC 0.55 V$GMEB 0.44 V$HASF -0.01 V$HAML 0.54 V$GZF1 0.42 V$WHNF -0.02 V$CIZF 0.53 V$ZF01 0.34 V$GTBX -0.03 V$TALE 0.52 O$TELO 0.27 V$GFI1 -0.04 V$ZF08 0.5 V$IKZF 0.24 V$PERO -0.05 V$YY1F 0.48 V$BCL6 0.17 O$TELO -0.06 V$GCNR 0.45 V$MYT1 0.12 V$PTF1 -0.06 V$BTBF 0.45 V$PCBE 0.02 V$DEAF -0.08 V$ZF06 0.37 V$IKRS -0.03 V$HZIP -0.15 V$ZFHX 0.36 V$OSRF -0.05 V$PAX1 -0.19 V$FXRE 0.31 O$TF3A -0.05 V$GMEB -0.28 V$GRHL 0.28 V$ZF08 -0.05 V$PCBE -0.37 V$PBXC 0.28 V$GFI1 -0.07 O$TF3C -0.38 V$GMEB 0.23 V$TCFF -0.12 V$ZF09 -0.39 V$THAP 0.2 V$PEG3 -0.14 V$CAAT -0.41 V$IKZF 0.16 V$CEBP -0.15 V$DUXF -0.44 V$ETSF 0.13 V$CSEN -0.22 V$RORA -0.45 V$HEAT -0.01 V$ZFXY -0.22 V$HOXH -0.45 V$MEF3 -0.03 V$TEAF -0.24 V$PAXH -0.46 V$ZF15 -0.05 V$CAAT -0.32 V$BCL6 -0.47 V$HUB1 -0.05 V$GUCE -0.38 V$TAIP -0.5 V$GUCE -0.26 V$HUB1 -0.41 V$OVOL -0.54 V$CHOP -0.34 V$BTBF -0.45 V$AP1F -0.54 V$MITF -0.39 V$BZIP -0.49 V$NBRE -0.55 V$CREB -0.57 V$PBXC -0.51 V$SIXF -0.58 V$ZF09 -0.58 V$STAT -0.56 V$ZF05 -0.58 V$ZBED -0.61 V$MEF3 -0.56 V$CHOP -0.61 V$OSRF -0.64 V$EREF -0.59 V$NR2F -0.66 V$PAX1 -0.66 V$LTFM -0.66 V$CHRF -0.69 V$PPAR -0.72 V$LTSM -0.73 V$PBXC -0.72 V$TEAF -0.82 V$ZF12 -0.73 V$FXRE -0.78 O$TF3C -1.02 V$HICF -0.73 V$SAL1 -0.83 V$BARB -1.07 V$BRAC -0.74 V$GZF1 -0.86 V$LTSM -1.07 V$CIZF -0.92 V$ZF08 -0.93 V$PROX -1.11 V$OVOL -0.93 V$BHLH -0.93 V$RP58 -1.13 V$ZF04 -1 V$GUCE -0.94 V$HZIP -1.14 V$HMTB -1.04 V$MYBL -0.95 V$AP1F -1.23 V$NEUR -1.09 V$STAT -0.96 V$ZF13 -1.29 V$BNCF -1.1 V$TCFF -1.05 O$TF2D -1.37 V$SAL1 -1.11 V$PEG3 -1.09 V$PCBE -1.44 V$THAP -1.11 V$GCNR -1.09 V$E4FF -1.47 V$ZF10 -1.17 V$CEBP -1.11 V$NFAT -1.51 V$AARF -1.23 V$PAX3 -1.12 V$GABF -1.65 V$ZF13 -1.25 V$PAX6 -1.12 V$SIX3 -1.75 V$MYRF -1.37 V$SIX3 -1.14 V$RU49 -1.8 O$TF3C -1.39 V$HMTB -1.16 V$CHRF -1.81 V$PTF1 -1.44 V$CIZF -1.18 V$ZF14 -1.82 V$HOXH -1.45 V$ZF10 -1.19 V$AARF -1.95 V$SRFF -1.5 V$PAX7 -1.2 V$ZF05 -1.96 V$RORA -1.51 V$PRDF -1.22 V$GFI1 -1.97 V$TAIP -1.54 V$PARF -1.26 V$OVOL -2.01 V$ZF14 -1.68 V$ZF14 -1.27 V$BCL6 -2.21 V$SNAP -1.72 V$SATB -1.28 V$PRDF -2.32 V$CREB -1.75 V$XBBF -1.29 V$ZF12 -2.43 V$ZF06 -1.81 V$IKZF -1.31 V$SIXF -2.56 V$RU49 -1.96 V$YY1F -1.34 V$HOXH -2.56 V$RP58 -2.01 V$PDX1 -1.34 V$CABL -2.63 V$E4FF -2.04 V$ATBF -1.35 V$ZF03 -2.69 V$CHRF -2.15 V$OSRF -1.38 V$TCFF -2.7 V$ZF03 -2.21 V$DLXF -1.38 V$CEBP -2.78 V$STEM -2.29 V$GATA -1.52 V$GZF1 -2.85 V$HAML -2.3 V$ETSF -1.67 V$STAT -2.93 V$SATB -2.35 V$BARB -1.73 V$MYBL -2.94 V$LEFF -2.42 V$SNAP -1.73 V$AIRE -3.08 V$HAND -2.46 V$BTBF -1.76 O$INRE -3.37 V$BPTF -2.49 V$ZF13 -1.77 V$BZIP -3.43 V$PAX2 -2.72 V$HUB1 -1.81 V$HMTB -3.58 V$GREF -2.78 V$PIT1 -1.82 V$SNAP -3.67 V$CLOX -2.86 V$HOMF -1.84 V$IRFF -3.74 V$PPAR -2.9 V$HEAT -1.85 V$SAL1 -3.79 V$PAX7 -3.06 V$AIRE -1.88 V$BHLH -3.83 V$ZF09 -3.08 V$HAML -1.91 V$HOXC -4.04 V$SIXF -3.25 V$MITF -1.97 V$DUXF -4.12 V$SIX3 -3.3 V$BCDF -2.01 V$BPTF -4.22 V$HNF6 -3.34 V$GREF -2.03 V$PAX7 -4.3 V$AIRE -3.47 O$INRE -2.07 V$RUSH -4.33 V$EVI1 -3.53 V$BPTF -2.17 V$EVI1 -4.41 V$DUXF -3.57 V$RP58 -2.19 V$FAST -4.62 V$RUSH -3.58 V$NKX6 -2.25 V$LEFF -4.71 V$ATBF -3.65 V$RU49 -2.26 V$PAX2 -4.76 O$VTBP -3.7 V$DMRT -2.27 V$ATBF -5.07 V$YY1F -3.75 V$MYT1 -2.28 V$IRXF -5.11 V$ZF05 -3.89 V$PLZF -2.3 V$SATB -5.21 V$PAXH -3.94 V$FAST -2.31 V$PLZF -5.25 V$GATA -3.98 V$HNF6 -2.64 V$PAXH -5.26 V$HNF1 -4.04 V$BZIP -2.68 V$CLOX -5.26 V$MITF -4.04 V$BRN5 -2.69 V$BCDF -5.35 V$FAST -4.07 V$ZF12 -2.74 V$NKX1 -5.43 V$CABL -4.27 V$LTSM -2.81 V$MYT1 -5.64 V$NKX1 -4.34 V$CART -2.96 V$PIT1 -6.14 V$PLZF -4.37 V$CABL -3 V$STEM -6.18 V$HOXC -4.55 V$RUSH -3 V$GATA -6.24 O$PTBP -4.59 V$LEFF -3.03 V$PDX1 -6.33 V$NKXH -4.63 V$IRFF -3.21 V$HNF6 -6.76 V$DLXF -4.63 V$ -3.24 V$NKXH -6.81 V$PDX1 -4.66 V$EVI1 -3.35 V$NKX6 -7.63 V$PIT1 -4.75 V$LHXF -3.35 V$MEF2 -7.7 V$BHLH -4.78 V$ARID -3.48 V$PARF -7.84 V$CDXF -4.88 V$HOXC -3.63 V$DLXF -7.95 V$PARF -4.91 V$HNF1 -3.78 V$DMRT -8.4 V$NKX6 -4.92 V$NKXH -3.83 V$CDXF -8.42 V$BCDF -4.99 V$HBOX -3.83 V$ARID -9.36 V$MEF2 -5.13 O$VTBP -3.86 V$HOXF -9.6 V$ABDB -5.41 V$STEM -3.97 V$HNF1 -9.82 V$HOMF -5.69 V$PAX2 -4.03 O$PTBP -10.06 O$YTBP -5.73 V$HOXF -4.04 O$YTBP -10.22 V$IRXF -6.08 V$CDXF -4.16 V$BRN5 -10.22 V$HBOX -6.55 O$PTBP -4.16 V$HBOX -10.24 V$DMRT -7.02 V$ABDB -4.33 V$LHXF -10.25 V$LHXF -7.85 V$IRXF -4.34 V$HOMF -10.39 V$OCT1 -8.07 V$FKHD -4.36 V$ABDB -10.41 V$BRN5 -8.08 O$YTBP -4.39 O$VTBP -10.74 V$ARID -8.15 V$CLOX -4.4 V$CART -11.93 V$HOXF -8.42 V$OCT1 -4.91 V$FKHD -12.17 V$BRNF -8.69 V$BRNF -5.39 V$BRNF -13 V$CART -8.91 V$SORY -8.43 V$OCT1 -13.44 V$SORY -9.6 V$SORY -17.17 V$FKHD -10.08

Table S7 – PROVIDED AS SEPARATE .XLS FILE Table S8. Details of primers and probes used for all quantitative PCR gene expression analysis.

NAME DESCRIPTION ACCESSION PROBE SEQUENCE 5' - 3' FORWARD PRIMER 5' - 3' REVERSE PRIMER 5' - 3'

ARG1 Arginase 1 NM_007482 SYBER GAAAGTTCCCAGATGTACCAGGAT CGATGTCTTTGGCAGATATGCA Fc recepter, igG, high affinity CD64 NM_007482 SYBER GAAAGTTCCCAGATGTACCAGGAT CGATGTCTTTGGCAGATATGCA I Macrophage scavenger CD204 NM_031195 SYBER GGAGGAGAGAATCGAAAGCATTT TCTGGAAGCGTTCCGTGTCT receptor 1 COLLAGEN 1 Procollagen type 1 NM_007742 6- FAM ATCGACCCTAACCAAG GACTGGAAGAGCGGAGAGTACTG CCTTGATGGCGTCCAGGTT COLLAGEN 3 Procollagen type 3 BC58724 6- FAM AATATCAAACACGCAAGGC GGGAATGGAGCAAGACAGTCTT TGCGATATCTATGATGGGTAGTCTCA COLLAGEN 4 Procollagen type 4 J04694 6- FAM CAGTGCCCTAACGGT GGCGGTACACAGTCAGACCAT GGAATAGCCGATCCACAGTGA CAAAAAGAAGAGAAAACCCACTATA COLLAGEN 4A3 Collagen 4 alpha 3 NM_007734 6-FAM CCCTGAAGGAACACAGC ACCACGGCCATTCCTTCAT GAGT Connective tissue growth CTGF BC006783 6- FAM ACTGCCTGGTCCAGAC GCTGCCTACCGACTGGAAGA CTTAGAACAGGCGCTCCACTCT factor F4/80 F4/80 X93328 SYBR GGTACAGTCATCTCCCTGGTATGTCT GGTTCTGAACAGCACGACACA FPR2 Formyl peptide receptor 2 NM_008039 6-FAM TGTGTTCTGCATCCAGTC GCCTTGGACCGCTGCAT TCACAGTGCGGTGGTTCTGA FPR2 Formyl peptide receptor 2 M88107 6-FAM CGCACAGTCACCACCAT TGGCTGGATTCCGGATGA AGGGCCAGGTTCAGGTAACA Intercellular adhesion ICAM1 NM_010493 6-FAM CCCTGGAACTGCACG GGAGGTGGCGGGAAAGTT TCCAGCCGAGGACCATACAG molecule 1 IL-1 beta Interleukin 1 beta M15131 6- FAM CTGAAAGCTCTCCACCTC TCGTGCTGTCGGACCCATA TTGTTGGTTGATATTCTGTCCATTG

IL-6 Interleukin 6 NM_031168 6- FAM ATTGCCATTGCACAACT GGGAAATCGTGGAAATGAGAAA AAGTGCATCATCGTTGTTCATACA 1L-10 Interleukin 10 NM_010548 6-FAM CATGGCCCAGAAAT GATGCCCCAGGCAGAGAA CACCCAGGGAATTCAAATGC Monocyte chemoattractant MCP-1 NM_011333 6- FAM AATGGGTCCAGACATAC GTCTGTGCTGACCCCAAGAAG TGGTTCCGATCCAGGTTTTTA protein-1 Cyclin-dependent kinase p21 NM_007669 6-FAM AGAGCCACAGGCACC TCCACAGCGATATCCAGACATT CGGACATCACCAGGATTGG inhibitor 1A (p21) NFKappaB p65 Transcription factor p65, also M61909 6-FAM AGCTCAAGATCTGCCG TCTCACATCCGATTTTTGATAACC CGAGGCAGCTCCCAGAGTT (RelA) known as RelA p53 Nuclear oncoprotein p53 AF151353 6-FAM TTTGTATCCCGAGTATCTG CGTATCCGGGTGGAAGGAA GGCGAAAAGTCTGCCTGTCT Proliferating cell nuclear TCAAGAGAAAGTTTCAGACTATGAA PCNA X53068 6- FAM CACAGCTGTACTCCTGTTC AAATTCACCAGATGGCATCTTTATT antigen ATGA Platelet derived growth PDGF NM_011057 6- FAM TCGCGGAACCTC TGTAATCGCCGAGTGCAAGA CATTGCACATTGCGGTTATTG factor Platelet derived growth PDGF REC B NM_008809 6- FAM CCACCATGAAAGTGG TCACGGTCTGAGCCATTCG TCTGGCTGTCGATTTCAGCAT factor receptor beta Advanced glycosylation end RAGE NM_007425 6- FAM CACAGCCCGGATTG GCTGTAGCTGGTGGTCAGAACA CCCCTTACAGCTTAGCACAAGTG product specific receptor SMA-alpha Smooth muscle actin - alpha NM_007392 6- FAM TGCCAGATCTTTTCC GACGCTGAAGTATCCGATAGAACA GGCCACACGAAGCTCGTTAT Transforming growth factor - TGF-beta NM_011577 6- FAM AAAGCCCTGTATTCCGT GCAGTGGCTGAACCAAGGA GCAGTGAGCGCTGAATCGA beta TGF-beta TYPE 1 Transforming growth factor - D25540 6-FAM CATCACTAGATCGCCC CGTGTGCCAAATGAAGAGGAT AAGGTGGTGCCCTCTGAAATG REC beta type 1 receptor TNF-alpha Tumor necrosis factor - alpha NM_013693 6- FAM TCACCCACACCGTCAG GGCTGCCCCGACTACGT TTTCTCCTGGTATGAGATAGCAAATC Tumour Necrosis Factor TNFRSF11b NM_008764 6-FAM CGAACCTCACCACAGAG GCGTGCAGCGGCATCT TCAATCTCTTCTGGGCTGATCTT Receptor member 11b vascular cell adhesion VCAM L22354 6-FAM CCAAAATCCTGTGGAGCAG CTGCTCAAGTGATGGGATACCA ATCGTCCCTTTTTGTAGACATGAAG molecule-1 Vascular endothelial growth VEGF M95200 6- FAM CTGTACCTCCACCATGC GCACTGGACCCTGGCTTTACT ATGGGACTTCTGCTCTCCTTCTG factor

TABLE S9. PROVIDED AS SEPARATE .XLS FILE

SUPPLEMENTAL REFERENCES

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SIGNIFICANCE STATEMENT

Impaired resolution of inflammation underlies chronic conditions, including microvascular com- plications of diabetes such as diabetic kidney disease (DKD). Lipoxins (LXs) are lipid mediators that promote the resolution of inflammation. Here, we investigated the potential of LXA4 and a synthetic LX analogue (Benzo-LXA4) as therapeutics in a murine model of DKD (streptozotocin diabetic 2 2 ApoE / mouse). The development of diabetes- induced albuminuria, mesangial expansion, and collagen deposition was attenuated by LXs. Kidney transcriptome profiling defined a diabetic signa- ture, and LX-mediated transcriptome responses. Using human renal epithelial cells, we demonstrate that LXs attenuate Egr-1 activation. These data demonstrate for the first time that LXs can reverse established diabetic complications and support a therapeutic paradigm to promote the resolution of inflammation.