Insulin signaling is coordinated by insulin receptor substrates (IRSs). Many insulin responses, especially for blood glucose metabolism, are mediated primarily through
The insulin signaling pathway is a complex network that regulates a series of metabolic processes in a tissue-specific manner (Zhang and Liu, 2014). Insulin suppresses glucose production and increases glycogen synthesis in liver (Rui, 2014); promotes glucose and fatty acid uptake in skeletal muscle (Blaak, 2005); inhibits lipolysis and stimulates lipid biosynthesis in adipose tissues (Newsholme and Dimitriadis, 2001); and positively regulates insulin secretion and β-cell function (Kubota et al., 2004; Leibiger et al., 2008). It has been reported that any defects in the insulin signaling pathway will lead to hyperglycemia and insulin resistance (Kadowaki, 2000), which are important pathophysiological features of a pre-diabetic state (Benito, 2011).
Insulin signaling is coordinated by counter-regulatory signaling through tyrosine phosphorylation of insulin receptor substrates (IRSs) (White, 2003). Although the role of each of these substrates merits attention, researches had revealed that many insulin responses, especially for blood glucose metabolism and bone metabolism, are mediated largely through
MicroRNAs (miRNAs) are a class of small non-coding RNAs consisting of 20–23 nucleotides that regulate gene expression (Cheng et al., 2015; Giudice et al., 2016). They cause translational repression or transcriptional degradation by binding to complementary sites in their 3′ untranslated region (3′ UTR) of target mRNAs (Berindan-Neagoe et al., 2014; Rebustini et al., 2016). miRNAs play key roles in regulating several metabolic processes in pancreatic β-cells, such as insulin biosynthesis, insulin secretion, and β-cell survival (Guay and Regazzi, 2015; Mao et al., 2013). In addition, miRNAs lead dominant roles in cellular differentiation, proliferation, apoptosis, cholesterol biosynthesis, and cancer development (Fernandez-Hernando et al., 2013). It has been reported that miR-33a/b contributes to the regulation of fatty acid metabolism and insulin signaling (Davalos et al., 2011), and miR-503 inhibits adipogenesis through classical insulin signal of PI3K/AKT by targeting bone morphogenetic protein receptor 1a (Man et al., 2016).
To test the hypothesis that there was other IRSs compensating for the defects of insulin signaling pathway because of
Protocols for mouse experiments were approved by the Animal Ethics Committee of Central South University. Three-month-old
Body weights of the wild type (
In order to clearly get know of the relationship between miR-33 and insulin signaling pathway, we constructed fasting and re-feeding wild-type mouse models. In fasting mice group, mice (n = 3) were fasted and then re-fed, after 24 h of fasting, we re-fed these mice for another 24 h (n = 3). All the mice were sacrificed and the subcutaneous fat were isolated for RT-PCR analysis.
Liver, skeletal muscle, and subcutaneous adipose tissue of
PI3K activity was determined using a commercially available kit (Echelon Biosciences, USA). The liver, skeletal muscle, and subcutaneous adipose tissue of
Transfected primary liver cells of wild type mice, as well as liver and skeletal muscle tissues of
Bone marrow stromal cells (BMSCs) from 2-month-old mice were maintained with DMEM (Hyclone, Logan, USA) and primary liver cells from 1-month-old wild type mice were cultured with DMEM/F12 medium (Invitrogen Life Technologies, USA), containing 10% fetal bovine serum (Invitrogen), penicillin (100 U/ml) and streptomycin (100 mg/ml), cultured in humidified 5% CO2 atmosphere at 37°C. The medium was refreshed every 2–3 days and cells were spread after reaching to 90% confluence. After an overnight culture without serum, cells were stimulated with 100 nM insulin (Sigma, USA) for 10 min. In addition, in order to get know of the relative expression of miR-33 in the presence of insulin or absence of insulin, 100 nM insulin were added into the liver cells after reaching to 80–90% confluence in six-well plates for 2 h in experimental group, and the control group was with equal amount of 0.9% NaCl.
At the very beginning of this research, we found the size of
The online software program TargetScan was used to predict the target genes of miR-33 with reference to the mouse gene sequence. The target genes predicted with the software program were intersected for further analysis. The software program website for target gene prediction is: TargetScanMouse
Mimic and inhibitor oligonucleotides of mmu-miR-33 and the negative control were synthesized by Yingrun Technology Corporation (China). The
Primary cultured liver cells of 1-month-old wild type mice were isolated and cultured in 6-well plates to 70% confluence, then the miR-33 mimic (50 nmol l−1) and inhibitor (100 nmol l−1) were transfected into the cells with Lipofectamine 2000 (Invitrogen) with the help of Opti-MEM I (Invitrogen). All experimental control samples were treated with an equal concentration of a mimic negative control sequence or an inhibitor negative control sequence (NC) to control for nonsequence-specific effects in the miRNA experiments. After 4–6 h, the cells were refreshed with normal growth medium. The cells were cultured for another 2 days at 37°C, and then subjected to the further analyses.
Total RNA from tissues or cultured cells was isolated using the TRIzol reagent (Invitrogen), and reverse transcription was performed using 1 μg of total RNA and SuperScript II (Invitrogen). Amplification reactions were set up in 25 μl reaction volumes containing SYBR Green PCR Master Mix (PE Applied Biosystems, USA) and amplification primers. A 1 μl volume of cDNA was used in each amplification reaction and eventually we performed qRT-PCR using a Roche Molecular Light Cycler. Primer sequences were as follows:
One-way analysis of variance (ANOVA) with a post-hoc Bonferroni test between the three or more groups while Student’s
To investigate the mechanisms behind the decline in FBG in the
In order to further confirm the changes in expression of downstream insulin signaling proteins in
To verify the hypothesis that the alternate substrate protein was IRS-2, we extracted proteins from liver and skeletal muscle tissues of the three different genotypes mice. We found that IRS-2 protein levels, as well as the levels of the downstream insulin signaling proteins (i.e., PI3K regulatory subunit p85, p-AKT), were increased in
To discover the underlying mechanisms of the increased IRS-2 expression in diverse tissues of the
With TargetScan software and a dual-luciferase reporter gene assay, we confirmed that
To validate the relationship between miR-33 and
It is known that
As further evidence,
Insulin resistance leading to an insufficient compensatory increase in insulin secretion by β cells is the major etiology of type 2 diabetes mellitus (Papaetis et al., 2015). IRS-1 is a docking protein that combines with the insulin receptor, and plays a central role in stimulating insulin’s actions, including the binding and activation of PI3K, and the subsequent increase in glucose transport (Li et al., 2014). In subjects with non-insulin dependent diabetes mellitus, IRS-1 is notably reduced, and IRS-2 becomes the main docking protein for PI3K in subcutaneous adipose tissue (Rondinone et al., 1997). In this research, we found that IRS-2 protein expression was no statistical differences in subcutaneous fat between in
BMSCs are a kind of pluripotent stem cell which has the ability to self-renew and differentiate into functional cells such as osteoblasts, chondrocytes, adipocytes and so on (Fang et al., 2014; Li and Song, 2012). Therefore, we used BMSCs for the miRNA microarray analysis. The result of our miRNA microarray demonstrated that miR-33 was significantly down-regulated in BMSCs from
In conclusion, considering the fact that miR-33 is intimately associated with the insulin signaling pathway led by