Triterpenoid CDDO-Me blocks the NF-kappaB pathway by direct inhibition of IKKbeta on Cys-179

The novel oleanane triterpenoid 2-cyano-3,12-dioxooleana-1,9,-dien-28-oic acid (CDDO) and the C-28 methyl ester (CDDO-Me) induce apoptosis of human tumor cells by disruption of redox balance and are currently in clinical trials. The present studies show that CDDO and CDDO-Me block tumor necrosis factoralpha-induced targeting of NF-kappaB p65 to the nucleus. CDDO-Me also blocked tumor necrosis factor alpha-induced phosphorylation of IkappaBalpha. In concert with these results, we found that CDDO-Me inhibits IkappaBalpha kinasebeta (IKKbeta) activity in cells. In support of a direct mechanism, CDDO-Me inhibited recombinant IKKbeta activity in vitro. The results also demonstrate that (i) CDDO and CDDO-Me form adducts with IKKbeta, but not IKKbeta with mutation of Cys-179 to Ala, and (ii) CDDO-Me inhibits IKKbeta by a mechanism dependent on oxidation of Cys-179. These findings indicate that CDDO and CDDO-Me directly block IKKbeta activity and thereby the NF-kappaB pathway by interacting with Cys-179 in the IKKbeta activation loop.     

The antifungal protein PAF interferes with PKC/MPK and cAMP/PKA signalling of Aspergillus nidulans

The Penicillium chrysogenum antifungal protein PAF inhibits polar growth and induces apoptosis in Aspergillus nidulans. We report here that two signalling cascades are implicated in its antifungal activity. PAF activates the cAMP/protein kinase A (Pka) signalling cascade. A pkaA deletion mutant exhibited reduced sensitivity towards PAF. This was substantiated by the use of pharmacological modulators: PAF aggravated the effect of the activator 8‐Br‐cAMP and partially relieved the repressive activity of caffeine. Furthermore, the Pkc/mitogen‐activated protein kinase (Mpk) signalling cascade mediated basal resistance to PAF, which was independent of the small GTPase RhoA. Non‐functional mutations of both genes resulted in hypersensitivity towards PAF. PAF did not increase MpkA phosphorylation or induce enzymes involved in the remodelling of the cell wall, which normally occurs in response to activators of the cell wall integrity pathway. Notably, PAF exposure resulted in actin gene repression and a deregulation of the chitin deposition at hyphal tips of A. nidulans, which offers an explanation for the morphological effects evoked by PAF and which could be attributed to the interconnection of the two signalling pathways. Thus, PAF represents an excellent tool to study signalling pathways in this model organism and to define potential fungal targets to develop new antifungals.     

Recognition of pathogenic Yersinia enterocolitica by crystal violet binding and polymerase chain reaction

Cefsulodin-Irgasan-Novobiocin (CIN) agar is used for the selective isolation and enumeration of Yersinia enterocolitica from clinical specimens and food. The medium contains crystal violet and about 1 mmol l^-1 calcium and can be used for the phenotypic characterization of strains that carry a virulence plasmid. At 32°C, irrespective of pathogenicity, colonies are translucent with a pale pink centre surrounded by a transparent border ('bullseye'), while at 37°C pathogenic strains grow as calcium-dependent microcolonies which, because of crystal violet binding, are intensely coloured. These results were confirmed by the polymerase chain reaction with primers directed at the vir F gene, which is present only in pathogenic strains of Y. enterocolitica. Pathogenic strains of Y. enterocolitica can be recognized by growth at 37°C on Yersinia selective agar.     

DNA ploidy and chromosomal imbalances in invasive ductal breast cancer. A comparative study of DNA image cytometry and comparative genomic hybridization (CGH).

Chromosomal imbalances were analyzed in 62 breast cancers with different DNA ploidy by CGH. The results of DNA image cytometry and CGH are consistent with peridiploid and aneuploid cases. The peritetraploid tumors harbored a high number of chromosomal imbalances, as a hint for an unfavorable prognosis. The quantitative analysis of imbalances highlighted the role of different physical constituents of the chromosome, and of chromosomal losses in different DNA ploidy groups. The peritetraploid and aneuploid tumors differed from the peridiploid tumors in losses at 8p and 18q. The peritetraploid cancers exhibited more gains at 8q, the aneuploid tumors more losses at 17p than their peridiploid counterparts. The aneuploid cases differed from the peritetraploid tumors in a higher number of losses at 11q and 14q. Combinations of imbalances provide further insights into the genetic background of DNA ploidy. Hypotheses for the progression from peridiploid to nondiploid breast cancers are given.     

Skeletal muscle Nur77 expression enhances oxidative metabolism and substrate utilization

Mitochondrial dysfunction has been implicated in the pathogenesis of type 2 diabetes. Identifying novel regulators of mitochondrial bioenergetics will broaden our understanding of regulatory checkpoints that coordinate complex metabolic pathways. We previously showed that Nur77, an orphan nuclear receptor of the NR4A family, regulates the expression of genes linked to glucose utilization. Here we demonstrate that expression of Nur77 in skeletal muscle also enhances mitochondrial function. We generated MCK-Nur77 transgenic mice that express wild-type Nur77 specifically in skeletal muscle. Nur77-overexpressing muscle had increased abundance of oxidative muscle fibers and mitochondrial DNA content. Transgenic muscle also exhibited enhanced oxidative metabolism, suggestive of increased mitochondrial activity. Metabolomic analysis confirmed that Nur77 transgenic muscle favored fatty acid oxidation over glucose oxidation, mimicking the metabolic profile of fasting. Nur77 expression also improved the intrinsic respiratory capacity of isolated mitochondria, likely due to the increased abundance of complex I of the electron transport chain. These changes in mitochondrial metabolism translated to improved muscle contractile function ex vivo and improved cold tolerance in vivo. Our studies outline a novel role for Nur77 in the regulation of oxidative metabolism and mitochondrial activity in skeletal muscle.     

Identification of a Ca(2+)-pectate binding site on an apoplastic peroxidase

An apoplastic isoperoxidase from zucchini (APRX) was shown to bind strongly to polygalacturonic acid in their Ca(2)+-induced conformation. By homology modeling, we were able to identify a motif of four clustered arginines (positions 117, 262, 268, and 271) that could be responsible for this binding. To verify the role of these arginine residues in the binding process, we prepared three mutants of APRX (M1, R117S; M2, R262Q/R268S; and M3, R262Q/R268S/R271Q). APRX and the three mutants were expressed as recombinant glycoproteins by the baculovirus-insect cell system. This procedure yielded four active enzymes with similar molecular masses that were tested for their ability to bind Ca(2)+-pectate. Recombinant wild-type APRX exhibited an affinity for the pectic structure comparable to that of the native plant isoperoxidase. The mutations impaired binding depending on the number of arginine residues that were replaced. M1 and M2 showed intermediate affinities, whereas M3 did not bind at all. This was demonstrated using an in vitro binding test and on cell walls of hypocotyl cross-sections. It can be concluded that APRX bears a Ca(2)+-pectate binding site formed by four clustered arginines. This site could ensure that APRX is properly positioned in cell walls, using unesterified domains of pectins as a scaffold.     

The effect of monoterpenes on astaxanthin production by a mutant ofPhaffia rhodozyma

Summary The total pigment and astaxanthin content ofPhaffia rhodozyma increased with increasing concentrations -pinene up to 500 l -pinene/l. Above this concentration the total pigment and astaxanthin content as well as the biomass production decreased. The addition of 500 l -pinene/l increased the total pigment content from 1652 g/g to 2201 g/g and the astaxanthin content from 1554 g/g to 1883 g/g. A sharp decrease in maximum specific growth rate occurred above 150 l -pinene/l.     

Fusing Data Mining,Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

Background

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study.

Methods

The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators.

Results

After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001).

Conclusion

The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.