Mechanistic Insights into the Cholesterol-dependent Binding of Perfringolysin O-based Probes and Cell Membranes

Cholesterol distribution in the cell is maintained by both vesicular and non-vesicular sterol transport. Non-vesicular transport is mediated by the interaction of membrane-embedded cholesterol and water-soluble proteins. Small changes to the lipid composition of the membrane that do not change the total cholesterol content, can significantly affect how cholesterol interacts with other molecules at the surface of the membrane. The cholesterol-dependent cytolysin Perfringolysin O (PFO) constitutes a powerful tool to detect cholesterol in membranes, and the use of PFO-based probes has flourished in recent years. By using a non-lytic PFO derivative, we showed that the sensitivity of the probes for cholesterol can be tuned by modifications introduced directly in the membrane-interacting loops and/or by modifying residues away from the membrane-interacting domain. Through the use of these biosensors on live RAW 264.7 cells, we found that changes in the overall cholesterol content have a limited effect on the average cholesterol accessibility at the surface of the membrane. We showed that these exquisite biosensors report on changes in cholesterol reactivity at the membrane surface independently of the overall cholesterol content in the membrane

Adsorption and temperature-dependent decomposition of SO₂ on Cu(100) and Cu(111): A fast and high-resolution core-level spectroscopy study

The adsorption and temperature-dependent decomposition of SO2 on Cu(100) and Cu(111) have been studied by fast and high-resolution core-level photoemission. The analysis of the S 2p and O 1s data shows that molecular SO2 adsorption dominates at 170 K. On heating the SO2-covered surfaces to about room temperature, SO2 decomposes into SO+O+S. On further heating SO+O recombine to form SO2, which is the only species detected in corresponding temperature-programmed desorption (TPD) experiments. From the temperature- (time-) dependent S and O coverages a ‘‘TPD curve’’ can be constructed

Atomic contributions to the valence band photoelectron spectra of metal-free, iron and manganese phthalocyanines

The present work reports a photoelectron spectroscopy study of the low-energy region of the valence band of metal-free phthalocyanine (H2Pc) compared with those of iron phthalocyanine (FePc) and manganese phthalocyanine (MnPc). Density Functional Theory calculations have been used to resolve the atomic orbital composition of the valence spectra of all the phthalocyanines (Pcs) analyzed in this study. Moreover we show how the atomic character of the Highest Occupied Molecular Orbital (HOMO) is reflected on the outermost valence band binding energy region. The intensity related to the C 2p contributions, resulting in the HOMO for H2Pc and FePc and in the HOMO-1 for MnPc as described by the theoretical predictions is in very good agreement with the experimental results. The DFT simulations, discerning the atomic contribution to the density of states, indicate how the central metal atom interacts with the C and N atoms of the molecule, giving rise to different partial and total density of states for these three different Pc molecules

m-MTDATA on Au(111): Spectroscopic Evidence of Molecule-Substrate Interactions

The starburst π-conjugated molecule based on triphenylamine (TPA) building blocks, 4,4′,4″-tris(N-3-ethylphenyl-N-phenylamino)triphenylamine (C57H48N4, m-MTDATA), is widely used in optoelectronic devices due to its electron-donating properties. The electronic structure of m-MTDATA adsorbed on an Au(111) surface was investigated by means of photoelectron spectroscopy (PES) and near edge X-ray absorption fine structure (NEXAFS) spectroscopy. The results were further compared to gas-phase measurements and DFT calculations. Our results clearly indicate a significant molecule-substrate interaction that induces considerable modifications on the electronic structure of the adsorbate compared to the isolated molecule. The energy level alignment analysis shows that the HOMO-LUMO gap is filled by new interface states

Binational reflections on pathways to groundwater security in the Mexico-United States borderlands

Shared groundwater resources between Mexico and the United States are facing unprecedented stressors. We reflect on how to improve water security for groundwater systems in the border region. Our reflection begins with the state of groundwater knowledge, and the challenges groundwater resources face from a physical, societal and institutional perspective. We conclude that the extent of ongoing cooperation frameworks, joint and remaining research efforts, from which alternative strategies can emerge, still need to be developed. The way forward offers a variety of cooperation models as the future offers rather complex, shared and multidisciplinary water challenges to the Mexico–US borderlands

DiseaseMeth: a human disease methylation database

DNA methylation is an important epigenetic modification for genomic regulation in higher organisms that plays a crucial role in the initiation and progression of diseases. The integration and mining of DNA methylation data by methylation-specific PCR and genome-wide profiling technology could greatly assist the discovery of novel candidate disease biomarkers. However, this is difficult without a comprehensive DNA methylation repository of human diseases. Therefore, we have developed DiseaseMeth, a human disease methylation database (http://bioinfo.hrbmu.edu.cn/diseasemeth). Its focus is the efficient storage and statistical analysis of DNA methylation data sets from various diseases. Experimental information from over 14 000 entries and 175 high-throughput data sets from a wide number of sources have been collected and incorporated into DiseaseMeth. The latest release incorporates the gene-centric methylation data of 72 human diseases from a variety of technologies and platforms. To facilitate data extraction, DiseaseMeth supports multiple search options such as gene ID and disease name. DiseaseMeth provides integrated gene methylation data based on cross-data set analysis for disease and normal samples. These can be used for in-depth identification of differentially methylated genes and the investigation of gene–disease relationship

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

<p>Abstract</p> <p>Background</p> <p>In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low <it>p</it>-value. However, the interpretation of each single <it>p</it>-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, <it>game theory </it>has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions.</p> <p>Results</p> <p>In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called <it>Comparative Analysis of Shapley value </it>(shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability.</p> <p>Conclusion</p> <p>CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways.</p

Linking the Epigenome to the Genome: Correlation of Different Features to DNA Methylation of CpG Islands

DNA methylation of CpG islands plays a crucial role in the regulation of gene expression. More than half of all human promoters contain CpG islands with a tissue-specific methylation pattern in differentiated cells. Still today, the whole process of how DNA methyltransferases determine which region should be methylated is not completely revealed. There are many hypotheses of which genomic features are correlated to the epigenome that have not yet been evaluated. Furthermore, many explorative approaches of measuring DNA methylation are limited to a subset of the genome and thus, cannot be employed, e.g., for genome-wide biomarker prediction methods. In this study, we evaluated the correlation of genetic, epigenetic and hypothesis-driven features to DNA methylation of CpG islands. To this end, various binary classifiers were trained and evaluated by cross-validation on a dataset comprising DNA methylation data for 190 CpG islands in HEPG2, HEK293, fibroblasts and leukocytes. We achieved an accuracy of up to 91% with an MCC of 0.8 using ten-fold cross-validation and ten repetitions. With these models, we extended the existing dataset to the whole genome and thus, predicted the methylation landscape for the given cell types. The method used for these predictions is also validated on another external whole-genome dataset. Our results reveal features correlated to DNA methylation and confirm or disprove various hypotheses of DNA methylation related features. This study confirms correlations between DNA methylation and histone modifications, DNA structure, DNA sequence, genomic attributes and CpG island properties. Furthermore, the method has been validated on a genome-wide dataset from the ENCODE consortium. The developed software, as well as the predicted datasets and a web-service to compare methylation states of CpG islands are available at http://www.cogsys.cs.uni-tuebingen.de/software/dna-methylation/