Project description:Purpose: To clarify cellular and molecular mechanisms underlying impaired post-ischemic adaptive vascular responses and to evaluate reconstituted HDL (rHDL)-ApoA-I nanotherapy to rescue the defect in type 2 diabetic (T2DM) mouse model of hindlimb ischemia (HLI). Methods: Mice with beta-cell specific over-expression of insulin-like growth factor-2 in atherosclerotic background (IGF-II/ LDLR-/-ApoB100/100) with T2DM features were used in the study with C57BL/6J mice fed with a regular chow-diet (R36, Lactamin) serving as controls. Mice aged between 16 to 20 weeks were used in the study . Mice were anaesthetized with 1.5-2% isoflurane/air mixture during the surgical procedure. Hair was removed from the operation site and cleaned with sterile water. Single incision was made just above medial thigh and superficial femoral artery was separated from femoral vein and nerve. HLI was induced by unilateral ligation of femoral artery distal to the origin of the profunda femoral artery. The skin was closed with interrupted silk sutures. Mice were were administered with reconstituted ApoA-I nanoparticles with phosphatidyl serine core (rHDL) intravenously starting 2 days post-HLI with doses every 2 days until scarification with Saline injections serving as controls. Adductors muscle aortic endothelial cells (AECs) and Ischemic muscle Macrophages and Endothelial Cells (ECs) were isolated using a combination of magnetic assisted cell sorting and flow Cytometry using Macrophage (F4/80) and EC (CD-31) specific markers. Total RNA isolated from FACS sorted cells were used for RNA seq library preparation. Results: Cell-specific gene expression, flow cytometry and immunohistochemistry revealed a persistent Macrophage and Endothelial cell inflammation and a reduced anti-inflammatory M2-macrophage activation associated with impaired collateral remodelling and sprouting angiogenesis in T2DM mice. Furthermore, reconstituted HDL (rHDL)- ApoA-I was found to rescue impaired collateral remodelling and angiogenesis in T2DM mice through modulating EC and macrophage phenotypes. Conclusions: Our results suggest that an impaired collateral remodelling and sprouting angiogenesis in T2DM mice after HLI is associated with a persistent EC and macrophage inflammation and a reduced activation of anti-inflammatory M2-macrophage. Skewing the macrophage phenotype towards the pro-arteriogenic and pro-angiogenic anti-inflammatory M2-macrophages using reconstituted HDL (rHDL)-ApoA-I nanotherapy may serve as a potential therapeutic modality for T2DM PAD.

Project description:Objective: To define the role of epigenetics, particularly DNA methylation in adaptive vascular growth in hyperlipidemic and type 2 diabetic mouse models of hind limb ischemia Methods: Unilateral hindlimb ischemia was induced by ligating femoral artery proximal to the bifurcation of superficial and deep femoral artery. DNA was isolated from ischemic muscles collected at day 7 after ischemia induction using DNeasy Tissue kit (Qiagen). 5 Âµg of genomic DNA was sheared into small fragments with a mean size of 150 bp by using a Covarisâ¢ S2 sonicator System. Quality of the fragmentation was analyzed with Bioanalyzer. Fragmented DNA samples were used for preparation of DNA fragment libraries and sequenced on the SOLiD4 sequencing instrument on one flow cell for 50 bp reads. The sequencing reads were mapped to mus musculus genome build mm9. Data was analyzed by using Bioscope. The samples were normalized with the MEDIPS package in R/B Bioconductor. The analysis of CpG methylation was done primarily in the proximal promoter regions encompassing a region of â1kb upstream of the transcription start site (TSS) and +500 bp downstream of the TSS. Comparisons were performed between hyperlipidemic versus controls and diabetic versus controls to detect differentially methylated regions. R package Limma was used for performing the statistical testing between the groups. Results: When visualizing the whole normalized data the samples did not cluster according to the sample groups. Especially two samples from hyperlipidemic and diabetic ischemic muscles differed clearly from the rest of the samples. To detect the differentially methylated genes, stringent thresholds for p-values and fold change values were chosen to list a reasonable number of genes. Upon filtering, significant differences in the methylation patterns of the sample groups were observed. More importantly, when clustering only the filtered genes, the samples clustered clearly according to the sample groups giving evidence of condition-dependent behavior. Using a threshold of methylation fold change of >1.2 and p value <0.05, we identified 397 and 446 genes to be hypomethylated in hyperlipidemic and diabetic ischemic muscles respectively compared to controls. There were 46 genes commonly shared, but still having a unique pattern of hypomethylation in 371 and 394 genes in hyperlipidemic and diabetic ischemic muscles respectively compared to controls. Similarly, there were 371 and 394 genes hypermethylated in hyperlipidemic and diabetic ischemic respectively compared to controls. Interestingly, we found 264 genes to be commonly hypermethylated, whereas 107 and 130 genes were uniquely hypermethylated in hyperlipidemic and diabetic ischemic muscles respectively. Thus, proximal promoter methylation suggested a shared, yet distinct pattern of DNA methylation in ischemic muscles of hyperlipidemic and type 2 diabetic mice compared to controls. Out of 397 genes that were hypomethylated in hyperlipidemic ischemic muscle, 68 genes were shown to be upregulated in âproinflammatory M1 macrophagesâ as shown by recent studies. Similarly, out of the 371 hypermethylated genes 93 genes were shown to be upregulated in âanti-inflammatory and proangiogenic M2 macrophagesâ as described recently. Out of 446 hypomethylated genes in diabetic ischemic muscle, 65 genes were shown to be upregulated in âproinflammatory M1 macrophagesâ as shown recently. Similarly, out of 394 hypermethylated genes 105 genes were specifically upregulated in âanti-inflammatory and proangiogenic M2 macrophagesâ as shown recently. qRT-PCR analysis suggested an inverse relationship between proximal promoter hypermethylation and mRNA expression in a subset of M2 macrophage specific genes in hyperlipidemic and type 2 diabetic ischemic muscles compared to control ischemic muscles. Conclusions: Our results suggest a role of epigenetics particularly proximal promoter DNA methylation in macrophage polarization and their contribution to angiogenesis and tissue repair in hyperlipidemic and type 2 diabetic mouse models of hind limb ischemia. Epigenetics at the level of DNA methylation may act as a deciding factor in promoting a pro or anti-inflammatory phenotype of macrophages critical in cardiovascular diseases. Ischemic skeletal muscle DNA methylation sequencing of triplicate samples from C57BL/6J (WT) mice, hyperlipidemic mice (LDLR-/-ApoB100/100 , C57BL/6J background) and type 2 diabetic mice (IGF-II/LDLR-/-ApoB100/100 , C57BL/6J background) using SoliD4 sequencing platform

Project description:Objective: To define the role of epigenetics, particularly DNA methylation in adaptive vascular growth in hyperlipidemic and type 2 diabetic mouse models of hind limb ischemia Methods: Unilateral hindlimb ischemia was induced by ligating femoral artery proximal to the bifurcation of superficial and deep femoral artery. DNA was isolated from ischemic muscles collected at day 7 after ischemia induction using DNeasy Tissue kit (Qiagen). 5 µg of genomic DNA was sheared into small fragments with a mean size of 150 bp by using a Covaris™ S2 sonicator System. Quality of the fragmentation was analyzed with Bioanalyzer. Fragmented DNA samples were used for preparation of DNA fragment libraries and sequenced on the SOLiD4 sequencing instrument on one flow cell for 50 bp reads. The sequencing reads were mapped to mus musculus genome build mm9. Data was analyzed by using Bioscope. The samples were normalized with the MEDIPS package in R/B Bioconductor. The analysis of CpG methylation was done primarily in the proximal promoter regions encompassing a region of –1kb upstream of the transcription start site (TSS) and +500 bp downstream of the TSS. Comparisons were performed between hyperlipidemic versus controls and diabetic versus controls to detect differentially methylated regions. R package Limma was used for performing the statistical testing between the groups. Results: When visualizing the whole normalized data the samples did not cluster according to the sample groups. Especially two samples from hyperlipidemic and diabetic ischemic muscles differed clearly from the rest of the samples. To detect the differentially methylated genes, stringent thresholds for p-values and fold change values were chosen to list a reasonable number of genes. Upon filtering, significant differences in the methylation patterns of the sample groups were observed. More importantly, when clustering only the filtered genes, the samples clustered clearly according to the sample groups giving evidence of condition-dependent behavior. Using a threshold of methylation fold change of >1.2 and p value <0.05, we identified 397 and 446 genes to be hypomethylated in hyperlipidemic and diabetic ischemic muscles respectively compared to controls. There were 46 genes commonly shared, but still having a unique pattern of hypomethylation in 371 and 394 genes in hyperlipidemic and diabetic ischemic muscles respectively compared to controls. Similarly, there were 371 and 394 genes hypermethylated in hyperlipidemic and diabetic ischemic respectively compared to controls. Interestingly, we found 264 genes to be commonly hypermethylated, whereas 107 and 130 genes were uniquely hypermethylated in hyperlipidemic and diabetic ischemic muscles respectively. Thus, proximal promoter methylation suggested a shared, yet distinct pattern of DNA methylation in ischemic muscles of hyperlipidemic and type 2 diabetic mice compared to controls. Out of 397 genes that were hypomethylated in hyperlipidemic ischemic muscle, 68 genes were shown to be upregulated in ‘proinflammatory M1 macrophages’ as shown by recent studies. Similarly, out of the 371 hypermethylated genes 93 genes were shown to be upregulated in ‘anti-inflammatory and proangiogenic M2 macrophages’ as described recently. Out of 446 hypomethylated genes in diabetic ischemic muscle, 65 genes were shown to be upregulated in ‘proinflammatory M1 macrophages’ as shown recently. Similarly, out of 394 hypermethylated genes 105 genes were specifically upregulated in ‘anti-inflammatory and proangiogenic M2 macrophages’ as shown recently. qRT-PCR analysis suggested an inverse relationship between proximal promoter hypermethylation and mRNA expression in a subset of M2 macrophage specific genes in hyperlipidemic and type 2 diabetic ischemic muscles compared to control ischemic muscles. Conclusions: Our results suggest a role of epigenetics particularly proximal promoter DNA methylation in macrophage polarization and their contribution to angiogenesis and tissue repair in hyperlipidemic and type 2 diabetic mouse models of hind limb ischemia. Epigenetics at the level of DNA methylation may act as a deciding factor in promoting a pro or anti-inflammatory phenotype of macrophages critical in cardiovascular diseases.

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Differential promoter methylation of macrophage genes correlates with impaired vascular growth in ischemic muscles of hyperlipidemic and type 2 diabetic mice

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