Inhibition of S6K1 accounts partially for the anti-inflammatory effects of the arginase inhibitor L-norvaline

<p>Abstract</p> <p>Background</p> <p>Pharmacological inhibition of endothelial arginase-II has been shown to improve endothelial nitric oxide synthase (eNOS) function and reduce atherogenesis in animal models. We investigated whether the endothelial arginase II is involved in inflammatory responses in endothelial cells.</p> <p>Methods</p> <p>Human endothelial cells were isolated from umbilical veins and stimulated with TNFα (10 ng/ml) for 4 hours. Endothelial expression of the inflammatory molecules i.e. vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and E-selectin were assessed by immunoblotting.</p> <p>Results</p> <p>The induction of the expression of endothelial VCAM-1, ICAM-1 and E-selectin by TNFα was concentration-dependently reduced by incubation of the endothelial cells with the arginase inhibitor L-norvaline. However, inhibition of arginase by another arginase inhibitor S-(2-boronoethyl)-L-cysteine (BEC) had no effects. To confirm the role of arginase-II (the prominent isoform expressed in HUVECs) in the inflammatory responses, adenoviral mediated siRNA silencing of arginase-II knocked down the arginase II protein level, but did not inhibit the up-regulation of the adhesion molecules. Moreover, the inhibitory effect of L-norvaline was not reversed by the NOS inhibitor L-NAME and L-norvaline did not interfere with TNFα-induced activation of NF-κB, JNK, p38mapk, while it inhibited p70s6k (S6K1) activity. Silencing S6K1 prevented up-regulation of E-selectin, but not that of VCAM-1 or ICAM-1 induced by TNFα.</p> <p>Conclusion</p> <p>The arginase inhibitor L-norvaline exhibits anti-inflammatory effects independently of inhibition of arginase in human endothelial cells. The anti-inflammatory properties of L-norvaline are partially attributable to its ability to inhibit S6K1.</p

Dissection of a QTL Hotspot on Mouse Distal Chromosome 1 that Modulates Neurobehavioral Phenotypes and Gene Expression

A remarkably diverse set of traits maps to a region on mouse distal chromosome 1 (Chr 1) that corresponds to human Chr 1q21–q23. This region is highly enriched in quantitative trait loci (QTLs) that control neural and behavioral phenotypes, including motor behavior, escape latency, emotionality, seizure susceptibility (Szs1), and responses to ethanol, caffeine, pentobarbital, and haloperidol. This region also controls the expression of a remarkably large number of genes, including genes that are associated with some of the classical traits that map to distal Chr 1 (e.g., seizure susceptibility). Here, we ask whether this QTL-rich region on Chr 1 (Qrr1) consists of a single master locus or a mixture of linked, but functionally unrelated, QTLs. To answer this question and to evaluate candidate genes, we generated and analyzed several gene expression, haplotype, and sequence datasets. We exploited six complementary mouse crosses, and combed through 18 expression datasets to determine class membership of genes modulated by Qrr1. Qrr1 can be broadly divided into a proximal part (Qrr1p) and a distal part (Qrr1d), each associated with the expression of distinct subsets of genes. Qrr1d controls RNA metabolism and protein synthesis, including the expression of ∼20 aminoacyl-tRNA synthetases. Qrr1d contains a tRNA cluster, and this is a functionally pertinent candidate for the tRNA synthetases. Rgs7 and Fmn2 are other strong candidates in Qrr1d. FMN2 protein has pronounced expression in neurons, including in the dendrites, and deletion of Fmn2 had a strong effect on the expression of few genes modulated by Qrr1d. Our analysis revealed a highly complex gene expression regulatory interval in Qrr1, composed of multiple loci modulating the expression of functionally cognate sets of genes

Genetic network identifies novel pathways contributing to atherosclerosis susceptibility in the innominate artery

Abstract Background Atherosclerosis, the underlying cause of cardiovascular disease, results from both genetic and environmental factors. Methods In the current study we take a systems-based approach using weighted gene co-expression analysis to identify a candidate pathway of genes related to atherosclerosis. Bioinformatic analyses are performed to identify candidate genes and interactions and several novel genes are characterized using in-vitro studies. Results We identify 1 coexpression module associated with innominate artery atherosclerosis that is also enriched for inflammatory and macrophage gene signatures. Using a series of bioinformatics analysis, we further prioritize the genes in this pathway and identify Cd44 as a critical mediator of the atherosclerosis. We validate our predictions generated by the network analysis using Cd44 knockout mice. Conclusion These results indicate that alterations in Cd44 expression mediate inflammation through a complex transcriptional network involving a number of previously uncharacterized genes