81 research outputs found

    Identificación de genes regulados por el sistema CpxAR en Serratia marcescens

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    Los sistemas de dos componentes (TCS, pos sus siglas en inglés) son mecanismos de señalización utilizados por las bacterias para regular la expresión diferencial de múltiples genes. El sistema CpxAR es un TCS conservado cuya función se ha relacionado principalmente con la respuesta al estrés de envoltura, sin embargo, también se ha reportado que contribuye en la regulación de genes de virulencia y de resistencia a antibióticos en bacterias de importancia clínica. Serratia marcescens es un patógeno emergente que ha cobrado relevancia durante las últimas décadas debido al incremento en el número de infecciones y la letalidad de las mismas, aspecto asociada con la multi-resistencia intrínseca de esta bacteria. A la fecha se conoce muy poco sobre el sistema CpxAR de S. marcescens y los genes regulados por este TCS, no obstante, los antecedentes sugieren que la secuencia de DNA que reconoce CpxR se encuentra conservada entre bacterias relacionadas. Con el objetivo de identificar los posibles genes regulados por el sistema CpxAR en S. marcescens en este proyecto se utilizaron 2 motivos consenso a partir de secuencias de unión de CpxR previamente reportadas, estos 2 motivos se utilizaron para analizar el genoma de S. marcescens mediante el programa FIMO. La curación manual de los resultados obtenidos arrojó un total de 92 (motivo 1) y 109 (motivo 2) posibles genes blanco de CpxR en S. marcescens. Para validar experimentalmente la predicción de sitios de unión de CpxR en primer lugar se amplificó el gen cpxR a partir de DNA genómico de S. marcescens y se clonó en el plásmido pET19b. La construcción pET19b-cpxR se utilizó para purificar mediante cromatografía de afinidad una versión recombinante de His-CpxR. Por otra parte, se amplificó mediante PCR la región promotora de los genes slyA y ssmE (motivo 1), y mdtH y eepR (motivo 2). La interacción in vitro de His-CpxR con las regiones promotoras (PslyA, PssmE, PmdtH, y PeepR) se evaluó mediante ensayos de cambio en la movilidad electroforética (EMSA). Los resultados confirmaron la interacción de CpxR con los promotores correspondientes a los motivos 1 y 2. Adicionalmente, una mutante puntual espontánea de CpxR en la leucina 208 de la α-hélice 8, evidenció un papel importante de dicho residuo hidrofóbico en la interacción de CpxR con las moléculas de DNA. Los resultados obtenidos en este trabajo indican que el sistema CpxAR contribuye a la regulación de factores de virulencia y genes asociados con la resistencia a antimicrobianos en S. marcescens

    Immersed boundary-finite element model of fluid-structure interaction in the aortic root

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    It has long been recognized that aortic root elasticity helps to ensure efficient aortic valve closure, but our understanding of the functional importance of the elasticity and geometry of the aortic root continues to evolve as increasingly detailed in vivo imaging data become available. Herein, we describe fluid-structure interaction models of the aortic root, including the aortic valve leaflets, the sinuses of Valsalva, the aortic annulus, and the sinotubular junction, that employ a version of Peskin's immersed boundary (IB) method with a finite element (FE) description of the structural elasticity. We develop both an idealized model of the root with three-fold symmetry of the aortic sinuses and valve leaflets, and a more realistic model that accounts for the differences in the sizes of the left, right, and noncoronary sinuses and corresponding valve cusps. As in earlier work, we use fiber-based models of the valve leaflets, but this study extends earlier IB models of the aortic root by employing incompressible hyperelastic models of the mechanics of the sinuses and ascending aorta using a constitutive law fit to experimental data from human aortic root tissue. In vivo pressure loading is accounted for by a backwards displacement method that determines the unloaded configurations of the root models. Our models yield realistic cardiac output at physiological pressures, with low transvalvular pressure differences during forward flow, minimal regurgitation during valve closure, and realistic pressure loads when the valve is closed during diastole. Further, results from high-resolution computations demonstrate that IB models of the aortic valve are able to produce essentially grid-converged dynamics at practical grid spacings for the high-Reynolds number flows of the aortic root

    Phenotype MicroArray Profiling of Zymomonas mobilis ZM4

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    In this study, we developed a Phenotype MicroArray™ (PM) protocol to profile cellular phenotypes in Zymomonas mobilis, which included a standard set of nearly 2,000 assays for carbon, nitrogen, phosphorus and sulfur source utilization, nutrient stimulation, pH and osmotic stresses, and chemical sensitivities with 240 inhibitory chemicals. We observed two positive assays for C-source utilization (fructose and glucose) using the PM screen, which uses redox chemistry and cell respiration as a universal reporter to profile growth phenotypes in a high-throughput 96-well plate-based format. For nitrogen metabolism, the bacterium showed a positive test results for ammonia, aspartate, asparagine, glutamate, glutamine, and peptides. Z. mobilis appeared to use a diverse array of P-sources with two exceptions being pyrophosphate and tripolyphosphate. The assays suggested that Z. mobilis uses both inorganic and organic compounds as S-sources. No stimulation by nutrients was detected; however, there was evidence of partial inhibition by purines and pyrimidines, NAD, and deferoxamine. Z. mobilis was relatively resistant to acid pH, tolerating a pH down to about 4.0. It also tolerated phosphate, sulfate, and nitrate, but was rather sensitive to chloride and nitrite. Z. mobilis showed resistance to a large number of diverse chemicals that inhibit most bacteria. The information from PM analysis provides an overview of Z. mobilis physiology and a foundation for future comparisons of other wild-type and mutant Z. mobilis strains

    A physicochemical descriptor-based scoring scheme for effective and rapid filtering of kinase-like chemical space

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    <p>Abstract</p> <p>Background</p> <p>The current chemical space of known small molecules is estimated to exceed 10<sup>60 </sup>structures. Though the largest physical compound repositories contain only a few tens of millions of unique compounds, virtual screening of databases of this size is still difficult. In recent years, the application of physicochemical descriptor-based profiling, such as Lipinski's rule-of-five for drug-likeness and Oprea's criteria of lead-likeness, as early stage filters in drug discovery has gained widespread acceptance. In the current study, we outline a kinase-likeness scoring function based on known kinase inhibitors.</p> <p>Results</p> <p>The method employs a collection of 22,615 known kinase inhibitors from the ChEMBL database. A kinase-likeness score is computed using statistical analysis of nine key physicochemical descriptors for these inhibitors. Based on this score, the kinase-likeness of four publicly and commercially available databases, i.e., National Cancer Institute database (NCI), the Natural Products database (NPD), the National Institute of Health's Molecular Libraries Small Molecule Repository (MLSMR), and the World Drug Index (WDI) database, is analyzed. Three of these databases, i.e., NCI, NPD, and MLSMR are frequently used in the virtual screening of kinase inhibitors, while the fourth WDI database is for comparison since it covers a wide range of known chemical space. Based on the kinase-likeness score, a kinase-focused library is also developed and tested against three different kinase targets selected from three different branches of the human kinome tree.</p> <p>Conclusions</p> <p>Our proposed methodology is one of the first that explores how the narrow chemical space of kinase inhibitors and its relevant physicochemical information can be utilized to build kinase-focused libraries and prioritize pre-existing compound databases for screening. We have shown that focused libraries generated by filtering compounds using the kinase-likeness score have, on average, better docking scores than an equivalent number of randomly selected compounds. Beyond library design, our findings also impact the broader efforts to identify kinase inhibitors by screening pre-existing compound libraries. Currently, the NCI library is the most commonly used database for screening kinase inhibitors. Our research suggests that other libraries, such as MLSMR, are more kinase-like and should be given priority in kinase screenings.</p

    Transcriptomic and metabolomic profiling of Zymomonas mobilis during aerobic and anaerobic fermentations

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    <p>Abstract</p> <p>Background</p> <p><it>Zymomonas mobilis </it>ZM4 (ZM4) produces near theoretical yields of ethanol with high specific productivity and recombinant strains are able to ferment both C-5 and C-6 sugars. <it>Z. mobilis </it>performs best under anaerobic conditions, but is an aerotolerant organism. However, the genetic and physiological basis of ZM4's response to various stresses is understood poorly.</p> <p>Results</p> <p>In this study, transcriptomic and metabolomic profiles for ZM4 aerobic and anaerobic fermentations were elucidated by microarray analysis and by high-performance liquid chromatography (HPLC), gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) analyses. In the absence of oxygen, ZM4 consumed glucose more rapidly, had a higher growth rate, and ethanol was the major end-product. Greater amounts of other end-products such as acetate, lactate, and acetoin were detected under aerobic conditions and at 26 h there was only 1.7% of the amount of ethanol present aerobically as there was anaerobically. In the early exponential growth phase, significant differences in gene expression were not observed between aerobic and anaerobic conditions via microarray analysis. HPLC and GC analyses revealed minor differences in extracellular metabolite profiles at the corresponding early exponential phase time point.</p> <p>Differences in extracellular metabolite profiles between conditions became greater as the fermentations progressed. GC-MS analysis of stationary phase intracellular metabolites indicated that ZM4 contained lower levels of amino acids such as alanine, valine and lysine, and other metabolites like lactate, ribitol, and 4-hydroxybutanoate under anaerobic conditions relative to aerobic conditions. Stationary phase microarray analysis revealed that 166 genes were significantly differentially expressed by more than two-fold. Transcripts for Entner-Doudoroff (ED) pathway genes (<it>glk, zwf, pgl, pgk, and eno</it>) and gene <it>pdc</it>, encoding a key enzyme leading to ethanol production, were at least 30-fold more abundant under anaerobic conditions in the stationary phase based on quantitative-PCR results. We also identified differentially expressed ZM4 genes predicted by The Institute for Genomic Research (TIGR) that were not predicted in the primary annotation.</p> <p>Conclusion</p> <p>High oxygen concentrations present during <it>Z. mobilis </it>fermentations negatively influence fermentation performance. The maximum specific growth rates were not dramatically different between aerobic and anaerobic conditions, yet oxygen did affect the physiology of the cells leading to the buildup of metabolic byproducts that ultimately led to greater differences in transcriptomic profiles in stationary phase.</p

    The Role of the Frank–Starling Law in the Transduction of Cellular Work to Whole Organ Pump Function: A Computational Modeling Analysis

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    We have developed a multi-scale biophysical electromechanics model of the rat left ventricle at room temperature. This model has been applied to investigate the relative roles of cellular scale length dependent regulators of tension generation on the transduction of work from the cell to whole organ pump function. Specifically, the role of the length dependent Ca2+ sensitivity of tension (Ca50), filament overlap tension dependence, velocity dependence of tension, and tension dependent binding of Ca2+ to Troponin C on metrics of efficient transduction of work and stress and strain homogeneity were predicted by performing simulations in the absence of each of these feedback mechanisms. The length dependent Ca50 and the filament overlap, which make up the Frank-Starling Law, were found to be the two dominant regulators of the efficient transduction of work. Analyzing the fiber velocity field in the absence of the Frank-Starling mechanisms showed that the decreased efficiency in the transduction of work in the absence of filament overlap effects was caused by increased post systolic shortening, whereas the decreased efficiency in the absence of length dependent Ca50 was caused by an inversion in the regional distribution of strain
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