Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.     

Ischaemia alters the effects of cardiomyocyte‐derived extracellular vesicles on macrophage activation

Myocardial ischaemia is associated with an exacerbated inflammatory response, as well as with a deregulation of intercellular communication systems. Macrophages have been implicated in the maintenance of heart homeostasis and in the progression and resolution of the ischaemic injury. Nevertheless, the mechanisms underlying the crosstalk between cardiomyocytes and macrophages remain largely underexplored. Extracellular vesicles (EVs) have emerged as key players of cell‐cell communication in cardiac health and disease. Hence, the main objective of this study was to characterize the impact of cardiomyocyte‐derived EVs upon macrophage activation. Results obtained demonstrate that EVs released by H9c2 cells induced a pro‐inflammatory profile in macrophages, via p38MAPK activation and increased expression of iNOS, IL‐1β and IL‐6, being these effects less pronounced with ischaemic EVs. EVs derived from neonatal cardiomyocytes, maintained either in control or ischaemia, induced a similar pattern of p38MAPK activation, expression of iNOS, IL‐1β, IL‐6, IL‐10 and TNFα. Importantly, adhesion of macrophages to fibronectin was enhanced by EVs released by cardiomyocytes under ischaemia, whereas phagocytic capacity and adhesion to cardiomyocytes were higher in macrophages incubated with control EVs. Additionally, serum‐circulating EVs isolated from human controls or acute myocardial infarction patients induce macrophage activation. According to our model, in basal conditions, cardiomyocyte‐derived EVs maintain a macrophage profile that ensure heart homeostasis, whereas during ischaemia, this crosstalk is affected, likely impacting healing and post‐infarction remodelling.     

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Streptomycetes are filamentous soil bacteria that are used in industry for the production of enzymes and antibiotics. When grown in bioreactors, these organisms form networks of interconnected hyphae, known as pellets, which are heterogeneous in size. Here we describe a method to analyze and sort mycelial pellets using a Complex Object Parametric Analyzer and Sorter (COPAS). Detailed instructions are given for the use of the instrument and the basic statistical analysis of the data. We furthermore describe how pellets can be sorted according to user-defined settings, which enables downstream processing such as the analysis of the RNA or protein content. Using this methodology the mechanism underlying heterogeneous growth can be tackled. This will be instrumental for improving streptomycetes as a cell factory, considering the fact that productivity correlates with pellet size.     

Analysis of two distinct mycelial populations in liquid-grown Streptomyces cultures using a flow cytometry-based proteomics approach

Streptomycetes are proficient producers of enzymes and antibiotics. When grown in bioreactors, these filamentous microorganisms form mycelial pellets that consist of interconnected hyphae. We here employed a flow cytometry approach designed for large particles (COPAS) and demonstrate that liquid-grown Streptomyces cultures consist of two distinct populations of pellets. One population consists of mycelia with a constant mean diameter of approximately 260?μm, whereas the other population contains larger mycelia whose diameter depends on the strain, the age of the culture, and medium composition. Quantitative proteomics analysis revealed that 37 proteins differed in abundance between the two populations of pellets. Stress-related proteins and biosynthetic proteins for production of the calcium-dependent antibiotic were more abundant in the population of large mycelia, while proteins involved in DNA topology, modification, or degradation were overrepresented in the population of small mycelia. Deletion of genes for the cellulose synthase-like protein CslA and the chaplins affected the average size of the population of large pellets but not that of small pellets. Considering the fact that the production of enzymes and metabolites depends on pellet size, these results provide new leads toward rational strain design of Streptomyces strains tailored for industrial fermentations.     

A kinetic model of the cyclin E/Cdk2 developmental timer in Xenopus laevis embryos

Early cell cycles of Xenopus laevis embryos are characterized by rapid oscillations in the activity of two cyclin-dependent kinases. Cdk1 activity peaks at mitosis, driven by periodic degradation of cyclins A and B. In contrast, Cdk2 activity oscillates twice per cell cycle, despite a constant level of its partner, cyclin E. Cyclin E degrades at a fixed time after fertilization, normally corresponding to the midblastula transition. Based on published data and new experiments, we constructed a mathematical model in which: (1) oscillations in Cdk2 activity depend upon changes in phosphorylation, (2) Cdk2 participates in a negative feedback loop with the inhibitory kinase Wee1; (3) cyclin E is cooperatively removed from the oscillatory system; and (4) removed cyclin E is degraded by a pathway activated by cyclin E/Cdk2 itself. The model's predictions about embryos injected with Xic1, a stoichiometric inhibitor of cyclin E/Cdk2, were experimentally validated.     

Charge Transfer from Methylammonium Lead Iodide Perovskite to Organic Transport Materials: Efficiencies,Transfer Rates,and Interfacial Recombination

Perovskite‐based photovoltaics have been rapidly developed, with record power conversion efficiencies now exceeding 22%. In order to rationally design efficient and stable perovskite solar cells, it is important to understand not only charge trapping and recombination events, but also processes occurring at the perovskite/transport material (TM) interface, such as charge transfer and interfacial recombination. In this work, time‐resolved microwave conductivity measurements are performed to investigate these interfacial processes for methylammonium lead iodide and various state‐of‐the‐art organic TMs. A global kinetic model is developed, which accurately describes both the dynamics of excess charges in the perovskite layer and transfer to charge‐specific TMs. The authors conclude that for state‐of‐the‐art materials, such as Spiro‐OMeTAD and PCBM, the charge extraction efficiency is not significantly affected by intra‐band gap traps for trap densities under 10¹⁵ cm^–3. Finally, the transfer rates to C60, PCBM, EDOT‐OMeTPA, and Spiro‐OMeTAD are sufficient to outcompete second order recombination under excitation densities representative for illumination by AM1.5.     

Pharmacological analysis of a dopamine D(2Short):G(alphao) fusion protein expressed in Sf9 cells

A dopamine D(2Short) receptor:G(alphao) fusion protein was expressed in Sf9 cells using the baculovirus expression system. [(3)H]Spiperone bound to D(2Short):G(alphao) with a pK(d) approximately 10. Dopamine stimulated the binding of [(35)S]guanosine-5'-O-(3-thio)triphosphate (GTPgammaS) to D(2Short):G(alphao) expressed with Gbeta(1)gamma(2) (E(max)>460%; pEC(50) 5.43+/-0.06). Most of the putative D(2) antagonists behaved as inverse agonists (suppressing basal [(35)S]GTPgammaS binding) at D(2Short):G(alphao)/Gbeta(1)gamma(2) although (-)-sulpiride and ziprasidone were neutral antagonists. Competition of [(3)H]spiperone binding by dopamine and 10,11-dihydroxy-N-n-propylnorapomorphine revealed two binding sites of different affinities, even in the presence of GTP (100 micro M). The D(2Short):G(alphao) fusion protein is therefore a good model for characterising D(2) receptors.     

Affinity analysis of lectin interaction with immobilized C- and O- gylcosides studied by surface plasmon resonance assay

A biosensor based on the surface plasmon resonance (SPR) principle was used for kinetic analysis of lectin interactions with different immobilized saccharide structures. A novel affinity ligands beta-D-glycopyranosylmethylamines derived from common D-aldohexoses linked to the carboxymethyl dextran layer of the SPR sensor surface served for interactions with a wide range of lectins. The method of preparation and use of the beta-D-mannopyranosyl glycosylated sensor surface was described. The results of affinity analysis of lectin-ligand interactions were evaluated and compared with data obtained from measurements using commercially available p-aminophenyl alpha-D-glycopyranosides. Possible applications and advantages of C- and O-glycosylated SPR biosensors are discussed.