Distribution and biological role of the oligopeptide-binding protein (OppA) in Xanthomonas species

In this study we investigated the prevalence of the oppA gene, encoding the oligopeptide binding protein (OppA) of the major bacterial oligopeptide uptake system (Opp), in different species of the genus Xanthomonas. The oppA gene was detected in two Xanthomonas axonopodis strains among eight tested Xanthomonas species. The generation of an isogenic oppA-knockout derivative of the Xac 306 strain, showed that the OppA protein neither plays a relevant role in oligopeptide uptake nor contributes to the infectivity and multiplication of the bacterial strain in leaves of sweet orange (Citrus sinensis) and Rangpur lime (Citrus limonia). Taken together these results suggest that the oppA gene has a recent evolutionary history in the genus and does not contribute in the physiology or pathogenesis of X. axonopodis

The route to transcription initiation determines the mode of transcriptional bursting in E. coli

Transcription is fundamentally noisy, leading to significant heterogeneity across bacterial populations. Noise is often attributed to burstiness, but the underlying mechanisms and their dependence on the mode of promotor regulation remain unclear. Here, we measure E. coli single cell mRNA levels for two stress responses that depend on bacterial sigma factors with different mode of transcription initiation (σ70 and σ54). By fitting a stochastic model to the observed mRNA distributions, we show that the transition from low to high expression of the σ70-controlled stress response is regulated via the burst size, while that of the σ54-controlled stress response is regulated via the burst frequency. Therefore, transcription initiation involving σ54 differs from other bacterial systems, and yields bursting kinetics characteristic of eukaryotic systems

A seesaw model for intermolecular gating in the kinesin motor protein

Recent structural observations of kinesin-1, the founding member of the kinesin group of motor proteins, have led to substantial gains in our understanding of this molecular machine. Kinesin-1, similar to many kinesin family members, assembles to form homodimers that use alternating ATPase cycles of the catalytic motor domains, or “heads”, to proceed unidirectionally along its partner filament (the microtubule) via a hand-over-hand mechanism. Cryo-electron microscopy has now revealed 8-Å resolution, 3D reconstructions of kinesin-1•microtubule complexes for all three of this motor’s principal nucleotide-state intermediates (ADP-bound, no-nucleotide, and ATP analog), the first time filament co-complexes of any cytoskeletal motor have been visualized at this level of detail. These reconstructions comprehensively describe nucleotide-dependent changes in a monomeric head domain at the secondary structure level, and this information has been combined with atomic-resolution crystallography data to synthesize an atomic-level "seesaw" mechanism describing how microtubules activate kinesin’s ATP-sensing machinery. The new structural information revises or replaces key details of earlier models of kinesin’s ATPase cycle that were based principally on crystal structures of free kinesin, and demonstrates that high-resolution characterization of the kinesin–microtubule complex is essential for understanding the structural basis of the cycle. I discuss the broader implications of the seesaw mechanism within the cycle of a fully functional kinesin dimer and show how the seesaw can account for two types of "gating" that keep the ATPase cycles of the two heads out of sync during processive movement

In vivo and in silico determination of essential genes of Campylobacter jejuni

<p>Abstract</p> <p>Background</p> <p>In the United Kingdom, the thermophilic <it>Campylobacter </it>species <it>C. jejuni </it>and <it>C. coli </it>are the most frequent causes of food-borne gastroenteritis in humans. While campylobacteriosis is usually a relatively mild infection, it has a significant public health and economic impact, and possible complications include reactive arthritis and the autoimmune diseases Guillain-Barré syndrome. The rapid developments in "omics" technologies have resulted in the availability of diverse datasets allowing predictions of metabolism and physiology of pathogenic micro-organisms. When combined, these datasets may allow for the identification of potential weaknesses that can be used for development of new antimicrobials to reduce or eliminate <it>C. jejuni </it>and <it>C. coli </it>from the food chain.</p> <p>Results</p> <p>A metabolic model of <it>C. jejuni </it>was constructed using the annotation of the NCTC 11168 genome sequence, a published model of the related bacterium <it>Helicobacter pylori</it>, and extensive literature mining. Using this model, we have used <it>in silico </it>Flux Balance Analysis (FBA) to determine key metabolic routes that are essential for generating energy and biomass, thus creating a list of genes potentially essential for growth under laboratory conditions. To complement this <it>in silico </it>approach, candidate essential genes have been determined using a whole genome transposon mutagenesis method. FBA and transposon mutagenesis (both this study and a published study) predict a similar number of essential genes (around 200). The analysis of the intersection between the three approaches highlights the shikimate pathway where genes are predicted to be essential by one or more method, and tend to be network hubs, based on a previously published <it>Campylobacter </it>protein-protein interaction network, and could therefore be targets for novel antimicrobial therapy.</p> <p>Conclusions</p> <p>We have constructed the first curated metabolic model for the food-borne pathogen <it>Campylobacter jejuni </it>and have presented the resulting metabolic insights. We have shown that the combination of <it>in silico </it>and <it>in vivo </it>approaches could point to non-redundant, indispensable genes associated with the well characterised shikimate pathway, and also genes of unknown function specific to <it>C. jejuni</it>, which are all potential novel <it>Campylobacter </it>intervention targets.</p

In Vivo Structure of the E. coli FtsZ-ring Revealed by Photoactivated Localization Microscopy (PALM)

The FtsZ protein, a tubulin-like GTPase, plays a pivotal role in prokaryotic cell division. In vivo it localizes to the midcell and assembles into a ring-like structure-the Z-ring. The Z-ring serves as an essential scaffold to recruit all other division proteins and generates contractile force for cytokinesis, but its supramolecular structure remains unknown. Electron microscopy (EM) has been unsuccessful in detecting the Z-ring due to the dense cytoplasm of bacterial cells, and conventional fluorescence light microscopy (FLM) has only provided images with limited spatial resolution (200–300 nm) due to the diffraction of light. Hence, given the small sizes of bacteria cells, identifying the in vivo structure of the Z-ring presents a substantial challenge. Here, we used photoactivated localization microscopy (PALM), a single molecule-based super-resolution imaging technique, to characterize the in vivo structure of the Z-ring in E. coli. We achieved a spatial resolution of ∼35 nm and discovered that in addition to the expected ring-like conformation, the Z-ring of E. coli adopts a novel compressed helical conformation with variable helical length and pitch. We measured the thickness of the Z-ring to be ∼110 nm and the packing density of FtsZ molecules inside the Z-ring to be greater than what is expected for a single-layered flat ribbon configuration. Our results strongly suggest that the Z-ring is composed of a loose bundle of FtsZ protofilaments that randomly overlap with each other in both longitudinal and radial directions of the cell. Our results provide significant insight into the spatial organization of the Z-ring and open the door for further investigations of structure-function relationships and cell cycle-dependent regulation of the Z-ring

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves.The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats.We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data

The elegans of spindle assembly

The Caenorhabditis elegans one-cell embryo is a powerful system in which to study microtubule organization because this large cell assembles both meiotic and mitotic spindles within the same cytoplasm over the course of 1 h in a stereotypical manner. The fertilized oocyte assembles two consecutive acentrosomal meiotic spindles that function to reduce the replicated maternal diploid set of chromosomes to a single-copy haploid set. The resulting maternal DNA then unites with the paternal DNA to form a zygotic diploid complement, around which a centrosome-based mitotic spindle forms. The early C. elegans embryo is amenable to live-cell imaging and electron tomography, permitting a detailed structural comparison of the meiotic and mitotic modes of spindle assembly

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject