Cofactor-specific modulation of 11beta-hydroxysteroid dehydrogenase 1 inhibitor potency

11beta-hydroxysteroid dehydrogenase 1 regulates the tissue availability of cortisol by interconverting cortisone and cortisol. It is capable of functioning as both a reductase and a dehydrogenase depending upon the surrounding milieu. In this work, we have studied the reaction mechanism of a soluble form of human 11beta-hydroxysteroid dehydrogenase 1 and its mode of inhibition by potent and selective inhibitors belonging to three different structural classes. We found that catalysis follows an ordered addition with NADP(H) binding preceding the binding of the steroid. While all three inhibitors tested bound to the steroid binding pocket, they differed in their interactions with the cofactor NADP(H). Compound A, a pyridyl amide bound more efficiently to the NADPH-bound form of 11beta-hydroxysteroid dehydrogenase 1. Compound B, an adamantyl triazole, was unaffected by NADP(H) binding and the sulfonamide, Compound C, showed preferential binding to the NADP+ -bound form of 11beta-hydroxysteroid dehydrogenase 1. These differences were found to augment significant selectivity towards inhibition of the reductase reaction versus the dehydrogenase reaction. This selectivity may translate to differences in the in vivo effects of 11beta-hydroxysteroid dehydrogenase 1 inhibitors.     

Novel O-palmitolylated beta-E1 subunit of pyruvate dehydrogenase is phosphorylated during ischemia/reperfusion injury

Background  

During and following myocardial ischemia, glucose oxidation rates are low and fatty acids dominate as a source of oxidative metabolism. This metabolic phenotype is associated with contractile dysfunction during reperfusion. To determine the mechanism of this reliance on fatty acid oxidation as a source of ATP generation, a functional proteomics approach was utilized.     

Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis

Background

It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks.

Results

In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings.

Conclusion

We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to the development, aging and progressive pathogenesis of a complex disease where potential dependences between different experiment units might occurs.     

Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis

Background  

Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis.     

EDC3 phosphorylation regulates growth and invasion through controlling P‐body formation and dynamics

Regulation of mRNA stability and translation plays a critical role in determining protein abundance within cells. Processing bodies (P‐bodies) are critical regulators of these processes. Here, we report that the Pim1 and 3 protein kinases bind to the P‐body protein enhancer of mRNA decapping 3 (EDC3) and phosphorylate EDC3 on serine (S)161, thereby modifying P‐body assembly. EDC3 phosphorylation is highly elevated in many tumor types, is reduced upon treatment of cells with kinase inhibitors, and blocks the localization of EDC3 to P‐bodies. Prostate cancer cells harboring an EDC3 S161A mutation show markedly decreased growth, migration, and invasion in tissue culture and in xenograft models. Consistent with these phenotypic changes, the expression of integrin β1 and α6 mRNA and protein is reduced in these mutated cells. These results demonstrate that EDC3 phosphorylation regulates multiple cancer‐relevant functions and suggest that modulation of P‐body activity may represent a new paradigm for cancer treatment.