Highly Stable Plasmonic Nanostructures on a Nickel-Sputtered Glass and Polymeric Optical Fiber Sensors

Plasmonics - This study shows development of highly sensitive and stable localized surface plasmon resonance (LSPR)-active U-bent glass and polymeric optical fiber (GOF and POF) sensor probes by a...     

High-Throughput miRNA and mRNA Sequencing of Paired Colorectal Normal,Tumor and Metastasis Tissues and Bioinformatic Modeling of miRNA-1 Therapeutic Applications

MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are, so far, hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We validated six miRNAs in a large tissue screen containing 16 additional tumor entities and identified miRNA-1, miRNA-129, miRNA-497 and miRNA-215 as constantly de-regulated within the majority of cancers. Of these, we investigated miRNA-1 as representative in a systems-biology simulation of cellular cancer models implemented in PyBioS and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system, miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options.     

Accurate phylogenetic classification of variable-length DNA fragments

Metagenome studies have retrieved vast amounts of sequence data from a variety of environments leading to new discoveries and insights into the uncultured microbial world. Except for very simple communities, the encountered diversity has made fragment assembly and the subsequent analysis a challenging problem. A taxonomic characterization of metagenomic fragments is required for a deeper understanding of shotgun-sequenced microbial communities, but success has mostly been limited to sequences containing phylogenetic marker genes. Here we present PhyloPythia, a composition-based classifier that combines higher-level generic clades from a set of 340 completed genomes with sample-derived population models. Extensive analyses on synthetic and real metagenome data sets showed that PhyloPythia allows the accurate classification of most sequence fragments across all considered taxonomic ranks, even for unknown organisms. The method requires no more than 100 kb of training sequence for the creation of accurate models of sample-specific populations and can assign fragments >or=1 kb with high specificity.     

Relation between Pulmonary Gas Exchange and Closing Volume before and after Substantial Weight Loss in Obese Subjects

Relations between expiratory reserve volume (ERV), closing volume (CV) as a percentage of vital capacity (CV/VC%), and pulmonary gas exchange have been investigated in the sitting and supine postures in eight severely obese subjects before and after substantial weight loss. CV/VC% exceeded predicted values but did not change with posture or weight loss; the increase could have been owing to the smoking habits of the subjects. Arterial oxygen pressure (PaO₂) was significantly less in the supine than in the sitting posture and improved after weight loss in six subjects. The reduction in PaO₂ was correlated with the extent to which dependent airways were closed within the range of tidal breathing, shown by increasing negativity of ERV-CV as a percentage of VC. A good correlation was also found between PaO₂ and ERV, an easier measurement for routine use. Improvement of pulmonary gas exchange occurred only in those patients who lost weight to within 30% in excess of ideal.     

Development of joint application strategies for two microbial gene finders

MOTIVATION: As a starting point in annotation of bacterial genomes, gene finding programs are used for the prediction of functional elements in the DNA sequence. Due to the faster pace and increasing number of genome projects currently underway, it is becoming especially important to have performant methods for this task. RESULTS: This study describes the development of joint application strategies that combine the strengths of two microbial gene finders to improve the overall gene finding performance. Critica is very specific in the detection of similarity-supported genes as it uses a comparative sequence analysis-based approach. Glimmer employs a very sophisticated model of genomic sequence properties and is sensitive also in the detection of organism-specific genes. Based on a data set of 113 microbial genome sequences, we optimized a combined application approach using different parameters with relevance to the gene finding problem. This results in a significant improvement in specificity while there is similarity in sensitivity to Glimmer. The improvement is especially pronounced for GC rich genomes. The method is currently being applied for the annotation of several microbial genomes. AVAILABILITY: The methods described have been implemented within the gene prediction component of the GenDB genome annotation system.     

Comparing expression level-dependent features in codon usage with protein abundance: an analysis of 'predictive proteomics'

Synonymous codon usage is a commonly used means for estimating gene expression levels of Escherichia coli genes and has also been used for predicting highly expressed genes for a number of prokaryotic genomes. By comparison of expression level-dependent features in codon usage with protein abundance data from two proteome studies of exponentially growing E. coli and Bacillus subtilis cells, we try to evaluate whether the implicit assumption of this approach can be confirmed with experimental data. Log-odds ratio scores are used to model differences in codon usage between highly expressed genes and genomic average. Using these, the strength and significance of expression level-dependent features in codon usage were determined for the genes of the Escherichia coli, Bacillus subtilis and Haemophilus influenzae genomes. The comparison of codon usage features with protein abundance data confirmed a relationship between these to be present, although exceptions to this, possibly related to functional context, were found. For species with expression level-dependent features in their codon usage, the applied methodology could be used to improve in silico simulations of the outcome of two-dimensional gel electrophoretic experiments.     

Ivermectin and nodulisporic acid receptors in Drosophila melanogaster contain both gamma-aminobutyric acid-gated Rdl and glutamate-gated GluCl alpha chloride channel subunits

35S-labeled derivatives of the insecticides nodulisporic acid and ivermectin were synthesized and demonstrated to bind with high affinity to a population of receptors in Drosophila head membranes that were previously shown to be associated with a glutamate-gated chloride channel. Nodulisporic acid binding was modeled as binding to a single population of receptors. Ivermectin binding was composed of at least two kinetically distinct receptor populations, only one of which was associated with nodulisporic acid binding. The binding of these two ligands was modulated by glutamate, ivermectin, and antagonists of invertebrate gamma-aminobutyric acid (GABA)ergic receptors. Because solubilized nodulisporic acid and ivermectin receptors comigrated as 230-kDa complexes by gel filtration, antisera specific for both the Drosophila glutamate-gated chloride channel subunit GluCl alpha (DmGluCl alpha) and the GABA-gated chloride channel subunit Rdl (DmRdl) proteins were generated and used to examine the possible coassembly of these two subunits within a single receptor complex. DmGluCl alpha antibodies immunoprecipitated all of the ivermectin and nodulisporic acid receptors solubilized by detergent from Drosophila head membranes. DmRdl antibodies also immunoprecipitated all solubilized nodulisporic receptors, but only approximately 70% of the ivermectin receptors. These data suggest that both DmGluCl alpha and DmRdl are components of nodulisporic acid and ivermectin receptors, and that there also exists a distinct class of ivermectin receptors that contains the DmGluCl alpha subunit but not the DmRdl subunit. This co-association of DmGluCl alpha and DmRdl represents the first biochemical and immunological evidence of coassembly of subunits from two different subclasses of ligand-gated ion channel subunits.     

Discovery of a novel class of biphenyl pyrazole sodium channel blockers for treatment of neuropathic pain

A series of novel biphenyl pyrazole dicarboxamides were identified as potential sodium channel blockers for treatment of neuropathic pain. Compound 20 had outstanding efficacy in the Chung rat spinal nerve ligation (SNL) model of neuropathic pain.     

Design and evaluation of 3,6-di(hetero)aryl imidazo[1,2-a]pyrazines as inhibitors of checkpoint and other kinases

A range of 3,6-di(hetero)arylimidazo[1,2-a]pyrazine ATP-competitive inhibitors of CHK1 were developed by scaffold hopping from a weakly active screening hit. Efficient synthetic routes for parallel synthesis were developed to prepare analogues with improved potency and ligand efficiency against CHK1. Kinase profiling showed that the imidazo[1,2-a]pyrazines could inhibit other kinases, including CHK2 and ABL, with equivalent or better potency depending on the pendant substitution. These 3,6-di(hetero)aryl imidazo[1,2-a]pyrazines appear to represent a general kinase inhibitor scaffold.     

GISMO--gene identification using a support vector machine for ORF classification

We present the novel prokaryotic gene finder GISMO, which combines searches for protein family domains with composition-based classification based on a support vector machine. GISMO is highly accurate; exhibiting high sensitivity and specificity in gene identification. We found that it performs well for complete prokaryotic chromosomes, irrespective of their GC content, and also for plasmids as short as 10 kb, short genes and for genes with atypical sequence composition. Using GISMO, we found several thousand new predictions for the published genomes that are supported by extrinsic evidence, which strongly suggest that these are very likely biologically active genes. The source code for GISMO is freely available under the GPL license.