A PLATFORM FOR THE DISCOVERY AND CHARACTERIZATION OF PROTEINS THAT ASSOCIATE WITH PSEUDOMONAS AERUGINOSA RNA POLYMERASE

Pseudomonas aeruginosa is an opportunistic bacterial pathogen notable for its ability to colonize the lungs of cystic fibrosis patients. Once the bacterium infects and colonizes humans, it is extremely difficult to eradicate. This leads to long-term infections that significantly damage the lungs and other tissues. P. aeruginosa infections are challenging to treat due to the bacterium’s natural antibiotic resistance and the rise of multidrug resistant strains. Development of novel drug treatments are a necessity. In all organisms, the regulation of gene expression is a highly controlled process. Remarkably, in P. aeruginosa bioinformatics studies showed that 20% of its genome is dedicated to regulating transcription, the first stage of gene expression. However, the vast majority of proteins that regulate transcription in P. aeruginosa are poorly understood. Understanding gene regulation is a promising strategy for discovery of novel drug targets. RNA polymerase (RNAP) is an essential enzyme controlling gene regulation, and its activity is modulated through a plethora of transcription factors or other proteins. The regulation of gene expression has been best studied in E. coli. The aim of this work was to develop a platform to study RNAP-interacting proteins in P. aeruginosa. To do this, we took advantage of an E. coli RNAP “coreome” library. The RNAP “coreome” was a term developed to describe 38 different plasmids each expressing surface exposed regions of RNAP inputted into a bacterial two-hybrid assay. In general, RNAP is a highly conserved enzyme among bacteria. Alignments of the amino acids of each piece of the E. coli RNAP coreome to specific domains of P. aeruginosa RNAP have shown a high degree of similarity (between 82-100%). The coreome was constructed based on the high-resolution structure of the bacteria Thermus aquaticus RNAP suggesting that E. coli β RNAP can be parsed into 10 sub-domains. Analysis of the E. coli β’ subunit of RNAP suggested that it could be parsed into 18 sub-domains that cover the entire gene (Nickels, 2009). A bacterial two-hybrid assay can be utilized to determine if a specific target protein interacts with domains of RNAP found within the RNAP coreome. Data from the IntAct Molecular Interaction Database identified 147 E. coli proteins that directly or indirectly interact with RNAP. We performed a bioinformatic analyses to identify P. aeruginosa homologs to these E. coli proteins. Initially, sixteen P. aeruginosa proteins were screened against the E. coli RNAP coreome in the bacterial two-hybrid assay. In this work five P. aeruginosa proteins, AlgQ, NusG, ClpA, DppF, and Tig were shown to interact with particular fragments of the E. coli RNAP coreome. Specifically, we show that AlgQ interacted with σ 528-613, NusG interacted with β’249-328 and β’264-308, ClpA interacted with β 829-930 and β 831-1059, DppF interacted with β\u27 114-190 and β 1137-1226, and Tig interacted with β\u27 735-790 and β 450-530. These results indicate the E. coli RNAP coreome can be utilized to uncover RNAP-interacting proteins in P. aeruginosa and to discover the precise domains they contact. In the future if the RNAP-binding determinants or proteins that control expression of virulence factors are identified using the RNAP coreome, it may be possible to design novel drugs that either disrupt the function of those proteins or their interaction with RNAP. Ultimately, this could lead to improved treatment options for P. aeruginosa infections

Open reduction and internal fixation compared to closed reduction and external fixation in distal radial fractures: A randomized study of 50 patients

Background and purpose In unstable distal radial fractures that are impossible to reduce or to maintain in reduced position, the treatment of choice is operation. The type of operation and the choice of implant, however, is a matter of discussion. Our aim was to investigate whether open reduction and internal fixation would produce a better result than traditional external fixation

The multiplex bead array approach to identifying serum biomarkers associated with breast cancer

Introduction Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population. Methods Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex (TM) bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls. Results Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity. Conclusions The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. 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Commentary on the MID3 Good Practices Paper

Contains fulltext : 178217.pdf (publisher's version ) (Open Access)During the last 10 years the European Medicines Agency (EMA) organized a number of workshops on modeling and simulation, working towards greater integration of modeling and simulation (M&S) in the development and regulatory assessment of medicines. In the 2011 EMA - European Federation of Pharmaceutical Industries and Associations (EFPIA) Workshop on Modelling and Simulation, European regulators agreed to the necessity to build expertise to be able to review M&S data provided by companies in their dossier. This led to the establishment of the EMA Modelling and Simulation Working Group (MSWG). Also, there was agreement reached on the need for harmonization on good M&S practices and for continuing dialog across all parties. The MSWG acknowledges the initiative of the EFPIA Model-Informed Drug Discovery and Development (MID3) group in promoting greater consistency in practice, application, and documentation of M&S and considers the paper is an important contribution towards achieving this objective