Type-2 diabetes-induced changes in vascular extracellular matrix gene expression: Relation to vessel size

Weiwei Song,Adviye Ergul

doi:10.1186/1475-2840-5-3

Weiwei Song, Adviye Ergul

Open Access

https://doi.org/10.1186/1475-2840-5-3

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Abstract

BackgroundHyperglycemia-induced changes in vascular wall structure contribute to the pathogenesis of diabetic microvascular and macrovascular complications. Matrix metalloproteinases (MMP), a family of proteolytic enzymes that degrade extracellular matrix (ECM) proteins, are essential for vascular remodeling. We have shown that endothelin-1 (ET-1) mediates increased MMP activity and associated vascular remodeling in Type 2 diabetes. However, the effect of Type 2 diabetes and/or ET-1 on the regulation of ECM and MMP gene expression in different vascular beds remains unknown.MethodsAorta and mesenteric artery samples were isolated from control, Type 2 diabetic Goto-Kakizaki (GK) rats and GK rats treated with ETA antagonist ABT-627. Gene expression profile of MMP-2, MMP-9, MT1-MMP, fibronectin, procollagen type 1, c-fos and c-jun, were determined by quantitative real-time (qRT) PCR. In addition, aortic gene expression profile was evaluated by an ECM & Adhesion Molecules pathway specific microarray approach.ResultsAnalysis of the qRT-PCR data demonstrated a significant increase in mRNA levels of MMPs and ECM proteins as compared to control animals after 6 weeks of mild diabetes. Futhermore, these changes were comparable in aorta and mesentery samples. In contrast, treatment with ETA antagonist prevented diabetes-induced changes in expression of MMPs and procollagen type 1 in mesenteric arteries but not in aorta. Microaarray analysis provided evidence that 27 extracellular matrix genes were differentially regulated in diabetes. Further qRT-PCR with selected 7 genes confirmed the microarray data.ConclusionThese results suggest that the expression of both matrix scaffold protein and matrix degrading MMP genes are altered in macro and microvascular beds in Type 2 diabetes. ETA antagonism restores the changes in gene expression in the mesenteric bed but not in aorta suggesting that ET-1 differentially regulates microvascular gene expression in Type 2 diabetes.

Highlights

Changes in vascular wall structure occur in diabetes and contribute to both micro- and macrovascular complications
While these studies provided evidence for diabetes-induced alterations in extracellular matrix (ECM) synthesis and vascular structure of an experimental model of Type 1 diabetes that is characterized by highly elevated blood glucose levels, to what extent mild-to-modest hyperglycemia as seen in Type 2 diabetes influences the gene expression of ECM proteins associated with vascular remodeling and whether there are differences in micro vs macrovascular bed are not fully understood
While decreased Matrix metalloproteinases (MMP) activity is generally believed to contribute to ECM accumulation in diabetic kidney and in vascular tissue from patients with diabetes, we and others have recently reported that there is an early activation of MMPs in hypertension and diabetes [7,8,9]

Summary

Methods

Animal and tissue preparation All experiments were performed on male Wistar (Harlan, Indianapolis, IN) and Goto-Kakizaki (in-house bred, derived from the Tampa colony) rats [11]. CDNA gene expression array analysis The expression profile of extracellular matrix & adhesion molecules genes was analyzed using the non-radioactive GEArray Q series Mouse gene array (MM-010N, SuperArray Bioscience Corp., Frederick, MD). This array membrane is composed of 96 extracellular matrix & adhesion molecules genes, a plasmid pUC18 negative control, and four housekeeping genes including glyceraldehyde-3phosphate dehydrogenase (GAPDH), cyclophilin A, ribosomal protein L13a, and β-actin. Data analysis RT-PCR results were reported as relative gene expression and the fold change in target genes was determined by 2∆∆Ct method, where -∆∆Ct = (CtTarget - CtActin)GK - (CtTarget CtActin)control and Ct value = the cycle number that crosses signal threshold. For Array studies, relative gene expression was analyzed using the SAM (Statistical Analysis of Microarrays) software [13]

Results

Conclusion

Introduction

Results and discussion

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