Confinement of knotted polymers in a slit

We investigate the effect of knot type on the properties of a ring polymer confined to a slit. For relatively wide slits, the more complex the knot, the more the force exerted by the polymer on the walls is decreased compared to an unknotted polymer of the same length. For more narrow slits the opposite is true. The crossover between these two regimes is, to first order, at smaller slit width for more complex knots. However, knot topology can affect these trends in subtle ways. Besides the force exerted by the polymers, we also study other quantities such as the monomer-density distribution across the slit and the anisotropic radius of gyration.Comment: 9 pages, 6 figures, submitted for publicatio

Proteomic analysis of cytosolic proteins associated with petite mutations in Candida glabrata

The incidence of superficial or deep-seated infections due to Candida glabrata has increased markedly, probably because of the low intrinsic susceptibility of this microorganism to azole antifungals and its relatively high propensity to acquire azole resistance. To determine changes in the C. glabrata proteome associated with petite mutations, cytosolic extracts from an azole-resistant petite mutant of C. glabrata induced by exposure to ethidium bromide, and from its azole-susceptible parent isolate were compared by two-dimensional polyacrylamide gel electrophoresis. Proteins of interest were identified by peptide mass fingerprinting or sequence tagging using a matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometer. Tryptic peptides from a total of 160 Coomassie-positive spots were analyzed for each strain. Sixty-five different proteins were identified in the cytosolic extracts of the parent strain and 58 in the petite mutant. Among the proteins identified, 10 were higher in the mutant strain, whereas 23 were lower compared to the parent strain. The results revealed a significant decrease in the enzymes associated with the metabolic rate of mutant cells such as aconitase, transaldolase, and pyruvate kinase, and changes in the levels of specific heat shock proteins. Moreover, transketolase, aconitase and catalase activity measurements decreased significantly in the ethidium bromide-induced petite mutant. These data may be useful for designing experiments to obtain a better understanding of the nuclear response to impairment of mitochondrial function associated with this mutation in C. glabrata

eQuilibrator—the biochemical thermodynamics calculator

The laws of thermodynamics constrain the action of biochemical systems. However, thermodynamic data on biochemical compounds can be difficult to find and is cumbersome to perform calculations with manually. Even simple thermodynamic questions like ‘how much Gibbs energy is released by ATP hydrolysis at pH 5?’ are complicated excessively by the search for accurate data. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemical compounds and reactions with a simple and powerful online search and calculation interface. The web interface to eQuilibrator (http://equilibrator.weizmann.ac.il) enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metabolite concentrations. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standard formats. Here we describe the database characteristics and implementation and demonstrate its use

An Easy-To-Use Simulation Program Demonstrates Variations in Bacterial Cell Cycle Parameters Depending on Medium and Temperature

Many studies are performed on chromosome replication and segregation in Escherichia coli and other bacteria capable of complex replication with C phases spanning several generations. For such investigations an understanding of the replication patterns, including copy numbers of origins and replication forks, is crucial for correct interpretation of the results

A Feedback Quenched Oscillator Produces Turing Patterning with One Diffuser

Efforts to engineer synthetic gene networks that spontaneously produce patterning in multicellular ensembles have focused on Turing's original model and the “activator-inhibitor” models of Meinhardt and Gierer. Systems based on this model are notoriously difficult to engineer. We present the first demonstration that Turing pattern formation can arise in a new family of oscillator-driven gene network topologies, specifically when a second feedback loop is introduced which quenches oscillations and incorporates a diffusible molecule. We provide an analysis of the system that predicts the range of kinetic parameters over which patterning should emerge and demonstrate the system's viability using stochastic simulations of a field of cells using realistic parameters. The primary goal of this paper is to provide a circuit architecture which can be implemented with relative ease by practitioners and which could serve as a model system for pattern generation in synthetic multicellular systems. Given the wide range of oscillatory circuits in natural systems, our system supports the tantalizing possibility that Turing pattern formation in natural multicellular systems can arise from oscillator-driven mechanisms

Intracellular Water Exchange for Measuring the Dry Mass, Water Mass and Changes in Chemical Composition of Living Cells

We present a method for direct non-optical quantification of dry mass, dry density and water mass of single living cells in suspension. Dry mass and dry density are obtained simultaneously by measuring a cell’s buoyant mass sequentially in an H[subscript 2]O-based fluid and a D[subscript 2]O-based fluid. Rapid exchange of intracellular H[subscript 2]O for D[subscript 2]O renders the cell’s water content neutrally buoyant in both measurements, and thus the paired measurements yield the mass and density of the cell’s dry material alone. Utilizing this same property of rapid water exchange, we also demonstrate the quantification of intracellular water mass. In a population of E. coli, we paired these measurements to estimate the percent dry weight by mass and volume. We then focused on cellular dry density – the average density of all cellular biomolecules, weighted by their relative abundances. Given that densities vary across biomolecule types (RNA, DNA, protein), we investigated whether we could detect changes in biomolecular composition in bacteria, fungi, and mammalian cells. In E. coli, and S. cerevisiae, dry density increases from stationary to exponential phase, consistent with previously known increases in the RNA/protein ratio from up-regulated ribosome production. For mammalian cells, changes in growth conditions cause substantial shifts in dry density, suggesting concurrent changes in the protein, nucleic acid and lipid content of the cell.National Cancer Institute (U.S.). Physical Sciences-Oncology Center (U54CA143874)National Institutes of Health (U.S.) (Center for Cell Division Process Grant P50GM6876)National Institutes of Health (U.S.) (Contract R01CA170592)United States. Army Research Office (Institute for Collaborate Biotechnologies Contract W911NF-09-D-0001

Model Convolution: A Computational Approach to Digital Image Interpretation

Digital fluorescence microscopy is commonly used to track individual proteins and their dynamics in living cells. However, extracting molecule-specific information from fluorescence images is often limited by the noise and blur intrinsic to the cell and the imaging system. Here we discuss a method called “model-convolution,” which uses experimentally measured noise and blur to simulate the process of imaging fluorescent proteins whose spatial distribution cannot be resolved. We then compare model-convolution to the more standard approach of experimental deconvolution. In some circumstances, standard experimental deconvolution approaches fail to yield the correct underlying fluorophore distribution. In these situations, model-convolution removes the uncertainty associated with deconvolution and therefore allows direct statistical comparison of experimental and theoretical data. Thus, if there are structural constraints on molecular organization, the model-convolution method better utilizes information gathered via fluorescence microscopy, and naturally integrates experiment and theory

Transcriptional and Proteomic Analysis of the Aspergillus fumigatus ΔprtT Protease-Deficient Mutant

Aspergillus fumigatus is the most common opportunistic mold pathogen of humans, infecting immunocompromised patients. The fungus invades the lungs and other organs, causing severe damage. Penetration of the pulmonary epithelium is a key step in the infectious process. A. fumigatus produces extracellular proteases to degrade the host structural barriers. The A. fumigatus transcription factor PrtT controls the expression of multiple secreted proteases. PrtT shows similarity to the fungal Gal4-type Zn(2)-Cys(6) DNA-binding domain of several transcription factors. In this work, we further investigate the function of this transcription factor by performing a transcriptional and a proteomic analysis of the ΔprtT mutant. Unexpectedly, microarray analysis revealed that in addition to the expected decrease in protease expression, expression of genes involved in iron uptake and ergosterol synthesis was dramatically decreased in the ΔprtT mutant. A second finding of interest is that deletion of prtT resulted in the upregulation of four secondary metabolite clusters, including genes for the biosynthesis of toxic pseurotin A. Proteomic analysis identified reduced levels of three secreted proteases (ALP1 protease, TppA, AFUA_2G01250) and increased levels of three secreted polysaccharide-degrading enzymes in the ΔprtT mutant possibly in response to its inability to derive sufficient nourishment from protein breakdown. This report highlights the complexity of gene regulation by PrtT, and suggests a potential novel link between the regulation of protease secretion and the control of iron uptake, ergosterol biosynthesis and secondary metabolite production in A. fumigatus