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MicroRNAs in an Experimental Model of Physiologic Left Ventricular Hypertrophy: a Microarray-based Analysis

ABSTRACT: BACKGROUND - MicroRNAs (miRs) are a class of small non-coding RNAs that regulate gene expression. Transgenic models have proved that a single miR can induce pathological cardiac hypertrophy and failure. The roles of miRs in the genesis of physiologic left ventricular hypertrophy (LVH), however, are not well elucidated. OBJECTIVE - To evaluate miRs expression in an experimental model of exercise-induced LVH. METHODS - Male Balb/c mice were divided into sedentary (SED) and exercise (EXE) groups. Voluntary exercise was performed in odometer-monitored metal wheels during 35 days. Analyses were performed after 7 and 35 days of training, and consisted of transthoracic echocardiography, maximal exercise test, miRs microarray (miRBase v.16) and real-time qRT-PCR analysis. RESULTS - Left ventricular weight/body weight ratio increased by 7% in the EXE group at day 7 (p<0.01) and by 11% at 35 days of training (p<0.001) After 7 days of training, microarray identified 35 deregulated miRs: 20 had an increase in their expression and 15 were down-regulated (p=0.01). At day 35 of training, 25 miRs were deregulated: 15 were up-regulated and 10 had decreased their expression compared to the SED group (p<0.01). qRT-PCR confirmed an increase in miR-150 levels at both time points and a decrease in miR-26b, miR-27a and miR-143 after 7 days of voluntary exercise. CONCLUSIONS – We unraveled new miRs that can modulate physiological cardiac hypertrophy, particularly miR-26b, -150, 27a and -143. Our data also indicate that previously established regulatory gene pathways involved in pathological LVH are not deregulated in physiologic LVH.

ORGANISM(S): Mus musculus

PROVIDER: GSE52278 | GEO | 2014/06/01

SECONDARY ACCESSION(S): PRJNA227330

REPOSITORIES: GEO

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Project description:While the salutary effects of exercise training on conduit artery endothelial cells have been reported in animals and humans with cardiovascular risk factors or disease, whether a healthy endothelium is alterable with exercise training is less certain. The purpose of this study was to evaluate the impact of exercise training on transcriptional profiles in normal endothelial cells using a genome-wide microarray analysis. Brachial and internal mammary endothelial gene expression was compared between a group of healthy pigs that exercise-trained for 16-20 weeks (n=8) and a group that remained sedentary (n=8). We found that a total of 130 genes were up regulated and 84 genes down regulated in brachial artery endothelial cells with exercise training. In contrast, a total of 113 genes were up regulated and 31 genes down regulated in internal mammary artery endothelial cells (>1.5-fold and false discovery rate<15%). Although there was an overlap of 66 genes (59 up regulated and 7 down regulated with exercise training) between the brachial and internal mammary arteries, the identified endothelial gene networks and biological processes influenced by exercise training were distinctly different between the brachial and internal mammary arteries. These data indicate that a healthy endothelium is indeed responsive to exercise training and support the concept that the influence of physical activity on endothelial gene expression is not homogenously distributed throughout the vasculature. Brachial and internal mammary endothelial gene expression was compared between a group of healthy pigs that exercise-trained for 16-20 weeks (n=8) and a group that remained sedentary (n=8). The arteries were taken from the same animals, and after quality assessment, so there were 29 total arrays (15 unique pigs), 14 with an array for both the brachial artery and the internal mammary artery (IMA), and the remaining 1 having only brachial. One pig had bad RNA quality and is missing from both IMA and brachical. Therefore, there were 15 IMA (7 SED, 8 EX) and 14 brachial arrays (7 SED, 7 EX) that were used in this study.

Project description:Lifestyle disorders like obesity, type 2 diabetes (T2D), and cardiovascular diseases can be prevented and treated by regular physical activity. During exercise, skeletal muscles release signaling factors that communicate with other organs and mediate beneficial effects of exercise. These factors include myokines, metabolites, and extracellular vesicles (EVs). In the present study, we have examined how electrical pulse stimulation (EPS) of myotubes, a model of exercise, affects the cargo of released EVs. Chronic low frequency EPS was applied for 24 h to human myotubes isolated and differentiated from biopsy samples from 6 morbidly obese females with T2D, and EVs, both exosomes and microvesicles (MV), were isolated from cell media 24 h thereafter. Size and concentration of EV subtypes were characterized by nanoparticle tracking analysis, surface markers were examined by flow cytometry and Western blotting, and morphology was confirmed by transmission electron microscopy. Protein content was assessed by high-resolution proteomic analysis (LC-MS/MS), non-coding RNA was quantified by Affymetrix microarray, and selected microRNAs (miRs) validated by real time RT-qPCR. The size and concentration of exosomes and MV were unaffected by EPS. Of the 400 miRs identified in the EVs, EPS significantly changed the level of 15 exosome miRs, of which miR-1233-5p showed the highest fold change. The miR pattern of MV was unaffected by EPS. Totally, about 1000 proteins were identified in exosomes and 2000 in MV. EPS changed the content of 73 proteins in exosomes, 97 in MVs, and of these 4 were changed in both exosomes and MV (GANAB, HSPA9, CNDP2, and ATP5B). By matching the EPS-changed miRs and proteins in exosomes, 31 targets were identified, and among these several promising signaling factors. Of particular interest were CNDP2, an enzyme that generates the appetite regulatory metabolite Lac-Phe, and miR-4433b-3p, which targets CNDP2. Several of the regulated miRs, such as miR-92b-5p, miR-320b, and miR-1233-5p might also mediate interesting signaling functions.

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MicroRNAs in an Experimental Model of Physiologic Left Ventricular Hypertrophy: a Microarray-based Analysis

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