BackgroundThere is increasing evidence that unacylated ghrelin (UAG) improves insulin sensitivity and glucose homeostasis; however, the mechanism for this activity is not fully understood since a UAG receptor has not been discovered.Methodology/Principal FindingsTo assess potential mechanisms of UAG action in vivo, we examined rapid effects of UAG on genome-wide expression patterns in fat, muscle and liver of growth hormone secretagogue receptor (GHSR)-ablated mice using microarrays. Expression data were analyzed using Ingenuity Pathways Analysis and Gene Set Enrichment Analysis. Regulation of subsets of these genes was verified by quantitative PCR in an independent experiment. UAG acutely regulated clusters of genes involved in glucose and lipid metabolism in all three tissues, consistent with enhancement of insulin sensitivity.Conclusions/SignificanceFat, muscle and liver are central to the control of lipid and glucose homeostasis. UAG rapidly modulates the expression of metabolically important genes in these tissues in GHSR-deleted mice indicating a direct, GHSR-independent, action of UAG to improve insulin sensitivity and metabolic profile.
Recent findings demonstrate that the effects of ghrelin can be abrogated by co-administered unacylated ghrelin (UAG). Since the general consensus is that UAG does not interact with the type 1a growth hormone secretagogue receptor (GHS-R), a possible mechanism of action for this antagonistic effect is via another receptor. However, functional antagonism of the GHS-R by UAG has not been explored extensively. In this study we used human GHS-R and aequorin expressing CHO-K1 cells to measure [Ca(2+)](i) following treatment with UAG. UAG at up to 10(-5)M did not antagonize ghrelin induced [Ca(2+)](i). However, UAG was found to be a full agonist of the GHS-R with an EC(50) of between 1.6 and 2 microM using this in vitro system. Correspondingly, UAG displaced radio-labeled ghrelin from the GHS-R with an IC(50) of 13 microM. In addition, GHS-R antagonists were found to block UAG induced [Ca(2+)](i) with approximately similar potency to their effect on ghrelin activation of the GHS-R, suggesting a similar mode of action. These findings demonstrate in a defined system that UAG does not antagonize activation of the GHS-R by ghrelin. But our findings also emphasize the importance of assessing the concentration of UAG used in both in vitro and in vivo experimental systems that are aimed at examining GHS-R independent effects. Where local concentrations of UAG may reach the high nanomolar to micromolar range, assignment of GHS-R independent effects should be made with caution.
Osteoporosis is a common skeletal disorder characterized by low bone mass leading to increased bone fragility and fracture susceptibility. Identification of factors influencing osteoblast differentiation and bone formation is very important. Previously, we identified parbendazole to be a novel compound that stimulates osteogenic differentiation of human mesenchymal stromal cells (hMSCs), using gene expression profiling and bioinformatic analyzes, including the Connectivity Map (CMap), as an in-silico approach. The aim for this paper is to identify additional compounds affecting osteoblast differentiation using the CMap. Gene expression profiling was performed on hMSCs differentiated to osteoblasts using Illumina microarrays. Our osteoblast gene signature, the top regulated genes 6 hr after induction by dexamethasone, was uploaded into CMap (www.broadinstitute.org/cmap/). Through this approach we identified compounds with gene signatures positively correlating (withaferin-A, calcium folinate, amylocaine) or negatively correlating (salbutamol, metaraminol, diprophylline) to our osteoblast gene signature. All positively correlating compounds stimulated osteogenic differentiation, as indicated by increased mineralization compared to control treated cells. One of three negatively correlating compounds, salbutamol, inhibited dexamethasone-induced osteoblastic differentiation, while the other two had no effect. Based on gene expression data of withaferin-A and salbutamol, we identified HMOX1 and STC1 as being strongly differentially expressed . shRNA knockdown of HMOX1 or STC1 in hMSCs inhibited osteoblast differentiation. These results confirm that the CMap is a powerful approach to identify positively compounds that stimulate osteogenesis of hMSCs, and through this approach we can identify genes that play an important role in osteoblast differentiation and could be targets for novel bone anabolic therapies.
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