Differential miRNA Expression in Cells and Matrix Vesicles in Vascular Smooth Muscle Cells from Rats with Kidney Disease

Abstract

Vascular calcification is a complex process and has been associated with aging, diabetes, chronic kidney disease (CKD). Although there have been several studies that examine the role of miRNAs (miRs) in bone osteogenesis, little is known about the role of miRs in vascular calcification and their role in the pathogenesis of vascular abnormalities. Matrix vesicles (MV) are known to play in important role in initiating vascular smooth muscle cell (VSMC) calcification. In the present study, we performed miRNA microarray analysis to identify the dysregulated miRs between MV and VSMC derived from CKD rats to understand the role of post-transcriptional regulatory networks governed by these miRNAs in vascular calcification and to uncover the differential miRNA content of MV. The percentage of miRNA to total RNA was increased in MV compared to VSMC. Comparison of expression profiles of miRNA by microarray demonstrated 33 miRs to be differentially expressed with the majority (~ 57%) of them down-regulated. Target genes controlled by differentially expressed miRNAs were identified utilizing two different complementary computational approaches Miranda and Targetscan to understand the functions and pathways that may be affected due to the production of MV from calcifying VSMC thereby contributing to the regulation of genes by miRs. We found several processes including vascular smooth muscle contraction, response to hypoxia and regulation of muscle cell differentiation to be enriched. Signaling pathways identified included MAP-kinase and wnt signaling that have previously been shown to be important in vascular calcification. In conclusion, our results demonstrate that miRs are concentrated in MV from calcifying VSMC, and that important functions and pathways are affected by the miRs dysregulation between calcifying VSMC and the MV they produce. This suggests that miRs may play a very important regulatory role in vascular calcification in CKD by controlling an extensive network of post-transcriptional targets.

Fig 1. Flowchart showing the various steps involved in this study.

Flowchart summarizing the sequence of analyses performed in this study.

Fig 2. miRNA is concentrated in MV compared to VSMC from CKD rats.

Total RNA from VSMC or MV was isolated from CKD rats and quantification performed using Agilent 2100 Bioanalyzer total and Small RNA kit. The results demonstrated that the total RNA level (A) is greater but miRNA levels are lower in VSMC compared to MV (B). n = 3, Data were expressed as mean±SEM, *p<0.05, MV vs. VSMC.

Fig 3. The fold change in expression of 33 miRs dysregulated in MV compared to VSMC from CKD rats.

All the 33 miRs were filtered at p-value < = 0.001 and FDR = 5% and isolated from 3 different rats Blue color represents the up-regulated miRs whereas the orange color represents the down-regulated miRs.

Fig 4. Network of up-regulated miRs and the targets (genes) controlled by them.

Red/orange nodes represent miRNA, with number corresponding to the table; the larger the node the more genes targeted. The green/yellow nodes represent genes regulated by these miRNA and the black lines the connectivity between miRNa and target genese. The highest degree which was observed to be 381 targets in this network. Network is generated using Cytoscape.

Fig 5. Network of down-regulated miRs and the targets (genes) controlled by them.

Color transition of the nodes is based on the degree (number of connections) of the nodes. Here nodes comprise both miRs and their targets. A table in the figure provides information about the nodes corresponding to the miRs. 0 represents lowest degree that is 1 and 1 corresponds to highest degree which was observed to be 262 targets in this network. Red color corresponds to the highest degree and green color corresponds to lowest degree. Network is generated using cytoscape.

Fig 6. Enrichment of biological functions in the gene set controlled by at least 3 miRs using ClueGo.

Analyses of those genese controlled by at least three miRNA were performed to identify important pathways. The genes were categorized based on ClueGo, a plugin of the cytoscape and all the functions reported are at p-value < = 0.05. The size of the nodes represents the number of miRNAs that regulate the genes, and the connectivity of multiple miRNAs regulating multiple genes within a common pathway are shown by the black lines. Purine biosynthesis and cAMP regulation demonstrated the most miRNA regulation (purple nodes).

Fig 7. RT-PCR validation of selected miRNAs n MV and VSMC.

To validate the miRNA identified by the arrays that regulate multiple genes, we performed Real time PCR on VSMc and MV to determine the expression of miR-667, miR-702, miR-3562, mir-3568 and miR-3584 and normalized by U6. Each sample (n = 3 with MV and VSMC isolated from 3 CKD rats, same samples as arrays) was assayed in triplicate. The results demonstrated increased expression in MV compared to VSMC for each of these miRNAs, confirming the array results. Data were expressed as mean ± SEM. * p<0.05, MV vs. VSMC.