Network Reconstruction Based on Proteomic Data and Prior Knowledge of Protein Connectivity Using Graph Theory

Modeling of signal transduction pathways is instrumental for understanding cells’ function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells’ biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways’ logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein–protein interaction networks and to provide meaningful biological insights.     

The Effect of Hole Transport Material Pore Filling on Photovoltaic Performance in Solid‐State Dye‐Sensitized Solar Cells

A detailed investigation of the effect of hole transport material (HTM) pore filling on the photovoltaic performance of solid‐state dye‐sensitized solar cells (ss‐DSCs) and the specific mechanisms involved is reported. It is demonstrated that the efficiency and photovoltaic characteristics of ss‐DSCs improve with the pore filling fraction (PFF) of the HTM, 2,2’,7,7’‐tetrakis‐(N, N ‐di‐ p ‐methoxyphenylamine)9,9’‐spirobifluorene(spiro‐OMeTAD). The mechanisms through which the improvement of photovoltaic characteristics takes place were studied with transient absorption spectroscopy and transient photovoltage/photocurrent measurements. It is shown that as the spiro‐OMeTAD PFF is increased from 26% to 65%, there is a higher hole injection efficiency from dye cations to spiro‐OMeTAD because more dye molecules are covered with spiro‐OMeTAD, an order‐of‐magnitude slower recombination rate because holes can diffuse further away from the dye/HTM interface, and a 50% higher ambipolar diffusion coefficient due to an improved percolation network. Device simulations predict that if 100% PFF could be achieved for thicker devices, the efficiency of ss‐DSCs using a conventional ruthenium‐dye would increase by 25% beyond its current value.     

Cannabinoid Modulation of Eukaryotic Initiation Factors (eIF2α and eIF2B1) and Behavioral Cross-Sensitization to Cocaine in Adolescent Rats

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Genomic divergence of zebu and taurine cattle identified through high-density SNP genotyping

Background

Natural selection has molded evolution across all taxa. At an arguable date of around 330,000 years ago there were already at least two different types of cattle that became ancestors of nearly all modern cattle, the Bos taurus taurus more adapted to temperate climates and the tropically adapted Bos taurus indicus. After domestication, human selection exponentially intensified these differences. To better understand the genetic differences between these subspecies and detect genomic regions potentially under divergent selection, animals from the International Bovine HapMap Experiment were genotyped for over 770,000 SNP across the genome and compared using smoothed F_ST. The taurine sample was represented by ten breeds and the contrasting zebu cohort by three breeds.

Results

Each cattle group evidenced similar numbers of polymorphic markers well distributed across the genome. Principal components analyses and unsupervised clustering confirmed the well-characterized main division of domestic cattle. The top 1% smoothed F_ST, potentially associated to positive selection, contained 48 genomic regions across 17 chromosomes. Nearly half of the top F_ST signals (n = 22) were previously detected using a lower density SNP assay. Amongst the strongest signals were the BTA7:~50 Mb and BTA14:~25 Mb; both regions harboring candidate genes and different patterns of linkage disequilibrium that potentially represent intrinsic differences between cattle types. The bottom 1% of the smoothed F_ST values, potentially associated to balancing selection, included 24 regions across 13 chromosomes. These regions often overlap with copy number variants, including the highly variable region at BTA23:~24 Mb that harbors a large number of MHC genes. Under these regions, 318 unique Ensembl genes are annotated with a significant overrepresentation of immune related pathways.

Conclusions

Genomic regions that are potentially linked to purifying or balancing selection processes in domestic cattle were identified. These regions are of particular interest to understand the natural and human selective pressures to which these subspecies were exposed to and how the genetic background of these populations evolved in response to environmental challenges and human manipulation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-876) contains supplementary material, which is available to authorized users.     

Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle

Background

Signatures of selection are regions in the genome that have been preferentially increased in frequency and fixed in a population because of their functional importance in specific processes. These regions can be detected because of their lower genetic variability and specific regional linkage disequilibrium (LD) patterns.

Methods

By comparing the differences in regional LD variation between dairy and beef cattle types, and between indicine and taurine subspecies, we aim at finding signatures of selection for production and adaptation in cattle breeds. The VarLD method was applied to compare the LD variation in the autosomal genome between breeds, including Angus and Brown Swiss, representing taurine breeds, and Nelore and Gir, representing indicine breeds. Genomic regions containing the top 0.01 and 0.1 percentile of signals were characterized using the UMD3.1 Bos taurus genome assembly to identify genes in those regions and compared with previously reported selection signatures and regions with copy number variation.

Results

For all comparisons, the top 0.01 and 0.1 percentile included 26 and 165 signals and 17 and 125 genes, respectively, including TECRL, BT.23182 or FPPS, CAST, MYOM1, UVRAG and DNAJA1.

Conclusions

The VarLD method is a powerful tool to identify differences in linkage disequilibrium between cattle populations and putative signatures of selection with potential adaptive and productive importance.     

Dynamic and facilitated binding of topoisomerase accelerates topological relaxation

How type 2 Topoisomerase (TopoII) proteins relax and simplify the topology of DNA molecules is one of the most intriguing open questions in genome and DNA biophysics. Most of the existing models neglect the dynamics of TopoII which is expected of proteins searching their targets via facilitated diffusion. Here, we show that dynamic binding of TopoII speeds up the topological relaxation of knotted substrates by enhancing the search of the knotted arc. Intriguingly, this in turn implies that the timescale of topological relaxation is virtually independent of the substrate length. We then discover that considering binding biases due to facilitated diffusion on looped substrates steers the sampling of the topological space closer to the boundaries between different topoisomers yielding an optimally fast topological relaxation. We discuss our findings in the context of topological simplification in vitro and in vivo.     

Impact of temperature on Na2Sr(PO4)F:Eu3+ phosphor

In this article, we report the synthesis of Na₂Sr_1‐x(PO₄)F:Eu_x phosphor via a combustion method. The influence of different annealing temperatures on the photoluminescence properties was investigated. The phosphor was excited at both 254 and 393 nm. Na₂Sr_1‐x(PO₄)F:Eu_x³⁺ phosphors emit strong orange and red color at 593 and 612 nm, respectively, under both excitation wavelengths. Na₂Sr_1‐x(PO₄)F:Eu_x³⁺ phosphors annealed at 1050°C showed stronger emission intensity compared with 600, 900 and 1200°C. Moreover, Na₂Sr_1‐x(PO₄)F:Eu_x³⁺ phosphor was found to be more intense when compared with commercial Y₂O₃:Eu³⁺ phosphor. Copyright © 2013 John Wiley & Sons, Ltd.     

Construction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data

Construction of large and cell-specific signaling pathways is essential to understand information processing under normal and pathological conditions. On this front, gene-based approaches offer the advantage of large pathway exploration whereas phosphoproteomic approaches offer a more reliable view of pathway activities but are applicable to small pathway sizes. In this paper, we demonstrate an experimentally adaptive approach to construct large signaling pathways from phosphoproteomic data within a 3-day time frame. Our approach--taking advantage of the fast turnaround time of the xMAP technology--is carried out in four steps: (i) screen optimal pathway inducers, (ii) select the responsive ones, (iii) combine them in a combinatorial fashion to construct a phosphoproteomic dataset, and (iv) optimize a reduced generic pathway via an Integer Linear Programming formulation. As a case study, we uncover novel players and their corresponding pathways in primary human hepatocytes by interrogating the signal transduction downstream of 81 receptors of interest and constructing a detailed model for the responsive part of the network comprising 177 species (of which 14 are measured) and 365 interactions.     

Symmetric cyanine dyes for detecting nucleic acids

A novel approach to the design of sensitive fluorescent probes for nucleic acids detection is proposed. Suitable modifications of tri- and pentamethine cyanine dyes in the polymethine chain and/or in the heterocyclic residues can result in a significant decrease in unbound dye fluorescence intensity and an increase in dye emission intensity in the presence of DNA compared to the unsubstituted dye. The sharp enhancement in the fluorescence intensity upon dye interaction with double-stranded DNA permits the application of the modified tri- and pentamethine dyes as fluorescent probes in double-stranded DNA detection in homogeneous assays.