Adaptive remodeling of the bacterial proteome by specific ribosomal modification regulates Pseudomonas infection and niche colonisation

Post-transcriptional control of protein abundance is a highly important, underexplored regulatory process by which organisms respond to their environments. Here we describe an important and previously unidentified regulatory pathway involving the ribosomal modification protein RimK, its regulator proteins RimA and RimB, and the widespread bacterial second messenger cyclic-di-GMP (cdG). Disruption of rimK affects motility and surface attachment in pathogenic and commensal Pseudomonas species, with rimK deletion significantly compromising rhizosphere colonisation by the commensal soil bacterium P. fluorescens, and plant infection by the pathogens P. syringae and P. aeruginosa. RimK functions as an ATP-dependent glutamyl ligase, adding glutamate residues to the C-terminus of ribosomal protein RpsF and inducing specific effects on both ribosome protein complement and function. Deletion of rimK in P. fluorescens leads to markedly reduced levels of multiple ribosomal proteins, and also of the key translational regulator Hfq. In turn, reduced Hfq levels induce specific downstream proteomic changes, with significant increases in multiple ABC transporters, stress response proteins and non-ribosomal peptide synthetases seen for both ΔrimK and Δhfq mutants. The activity of RimK is itself controlled by interactions with RimA, RimB and cdG. We propose that control of RimK activity represents a novel regulatory mechanism that dynamically influences interactions between bacteria and their hosts; translating environmental pressures into dynamic ribosomal changes, and consequently to an adaptive remodeling of the bacterial proteome

An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

<p>Abstract</p> <p>Background</p> <p>Patients diagnosed with lung adenocarcinoma (AD) and squamous cell carcinoma (SCC), two major histologic subtypes of lung cancer, currently receive similar standard treatments, but resistance to adjuvant chemotherapy is prevalent. Identification of differentially expressed genes marking AD and SCC may prove to be of diagnostic value and help unravel molecular basis of their histogenesis and biologies, and deliver more effective and specific systemic therapy.</p> <p>Methods</p> <p>MiRNA target genes were predicted by union of miRanda, TargetScan, and PicTar, followed by screening for matched gene symbols in NCBI human sequences and Gene Ontology (GO) terms using the PANTHER database that was also used for analyzing the significance of biological processes and pathways within each ontology term. Microarray data were extracted from Gene Expression Omnibus repository, and tumor subtype prediction by gene expression used Prediction Analysis of Microarrays.</p> <p>Results</p> <p>Computationally predicted target genes of three microRNAs, miR-34b/34c/449, that were detected in human lung, testis, and fallopian tubes but not in other normal tissues, were filtered by representation of GO terms and their ability to classify lung cancer subtypes, followed by a meta-analysis of microarray data to classify AD and SCC. Expression of a minimal set of 17 predicted miR-34b/34c/449 target genes derived from the developmental process GO category was identified from a training set to classify 41 AD and 17 SCC, and correctly predicted in average 87% of 354 AD and 82% of 282 SCC specimens from total 9 independent published datasets. The accuracy of prediction still remains comparable when classifying 103 AD and 79 SCC samples from another 4 published datasets that have only 14 to 16 of the 17 genes available for prediction (84% and 85% for AD and SCC, respectively). Expression of this signature in two published datasets of epithelial cells obtained at bronchoscopy from cigarette smokers, if combined with cytopathology of the cells, yielded 89–90% sensitivity of lung cancer detection and 87–90% negative predictive value to non-cancer patients.</p> <p>Conclusion</p> <p>This study focuses on predicted targets of three lung-enriched miRNAs, compares their expression patterns in lung cancer by their GO terms, and identifies a minimal set of genes differentially expressed in AD and SCC, followed by validating this gene signature in multiple published datasets. Expression of this gene signature in bronchial epithelial cells of cigarette smokers also has a great sensitivity to predict the patients having lung cancer if combined with cytopathology of the cells.</p

Guidelines for histopathological specimen examination and diagnostic reporting of primary bone tumours

This review is intended to provide histopathologists with guidelines for clinical assessment, specimen handling and diagnostic reporting of benign and malignant primary bone tumours. Information from radiology, surgical, oncology and other clinical colleagues involved in the diagnosis and treatment of primary bone tumours should be properly assessed before undertaking a structured approach to specimen handling and histological reporting. This ensures that the information needed for planning appropriate treatment of these complex tumours is provided. Consistency in diagnostic evaluation with respect to both terminology and report content facilitates liaison at multidisciplinary bone tumour meetings and collaboration between cancer units and networks, as well as providing a common database for audit of the clinical, radiological and pathological aspects of bone tumours

Site-specific uniform hazard spectrum in Eastern Turkey based on simulated ground motions including near-field directivity and detailed site effects

In this study, stochastic earthquake catalog of the Erzincan region in Turkey is generated based on synthetic ground motions. Monte Carlo simulation method is used to identify the spatial and temporal distribution of events. Ground motion time histories are generated using stochastic simulation methodology. Annual exceedance rate of each ground motion amplitude is calculated through statistical distribution of the complete set of ground motions. The results are compared with classical probabilistic seismic hazard analysis (PSHA). Classical PSHA generally produces larger spectral amplitudes than the proposed study due to wide range of aleatory variability. The effects of near-field forward directivity and detailed site response are also investigated on the results