Twin RNA Polymerase–Associated Proteins Control Virulence Gene Expression in Francisella tularensis

The MglA protein is the only known regulator of virulence gene expression in Francisella tularensis, yet it is unclear how it functions. F. tularensis also contains an MglA-like protein called SspA. Here, we show that MglA and SspA cooperate with one another to control virulence gene expression in F. tularensis. Using a directed proteomic approach, we show that both MglA and SspA associate with RNA polymerase (RNAP) in F. tularensis, and that SspA is required for MglA to associate with RNAP. Furthermore, bacterial two-hybrid and biochemical assays indicate that MglA and SspA interact with one another directly. Finally, through genome-wide expression analyses, we demonstrate that MglA and SspA regulate the same set of genes. Our results suggest that a complex involving both MglA and SspA associates with RNAP to positively control virulence gene expression in F. tularensis. The F. tularensis genome is unusual in that it contains two genes encoding different α subunits of RNAP, and we show here that these two α subunits are incorporated into RNAP. Thus, as well as identifying SspA as a second critical regulator of virulence gene expression in F. tularensis, our findings provide a framework for understanding the mechanistic basis for virulence gene control in a bacterium whose transcription apparatus is unique

Small Molecule Control of Virulence Gene Expression in Francisella tularensis

In Francisella tularensis, the SspA protein family members MglA and SspA form a complex that associates with RNA polymerase (RNAP) to positively control the expression of virulence genes critical for the intramacrophage growth and survival of the organism. Although the association of the MglA-SspA complex with RNAP is evidently central to its role in controlling gene expression, the molecular details of how MglA and SspA exert their effects are not known. Here we show that in the live vaccine strain of F. tularensis (LVS), the MglA-SspA complex works in concert with a putative DNA-binding protein we have called PigR, together with the alarmone guanosine tetraphosphate (ppGpp), to regulate the expression of target genes. In particular, we present evidence that MglA, SspA, PigR and ppGpp regulate expression of the same set of genes, and show that mglA, sspA, pigR and ppGpp null mutants exhibit similar intramacrophage growth defects and are strongly attenuated for virulence in mice. We show further that PigR interacts directly with the MglA-SspA complex, suggesting that the central role of the MglA and SspA proteins in the control of virulence gene expression is to serve as a target for a transcription activator. Finally, we present evidence that ppGpp exerts its effects by promoting the interaction between PigR and the RNAP-associated MglA-SspA complex. Through its responsiveness to ppGpp, the contact between PigR and the MglA-SspA complex allows the integration of nutritional cues into the regulatory network governing virulence gene expression

Controlling the assembly of cyclotriveratrylene-derived coordination cages

A review of the emerging field of cyclotriveratrylene-derived coordination cages is presented. Ligand-functionalised cyclotriveratrylene (CTV) derivatives self-assemble with a range of metal cations to afford coordination cages, polymers and topologically non-trivial constructs, such as [2]catenanes and a self-entangled cube. Increased control over their self-assembly allows for the controlled and predictable formation of well-defined coordination cages for application in host-guest and recognition chemistry, with surfactant binding and single-crystal-to-single-crystal (SCTSC) uptake of small-molecule guests being observed

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95)

A white-box anomaly-based framework for database leakage detection

Data leakage is at the heart most of the privacy breaches worldwide. In this paper we present a white-box approach to detect potential data leakage by spotting anomalies in database transactions. We refer to our solution as white-box because it builds self explanatory profiles that are easy to understand and update, as opposite to black-box systems which create profiles hard to interpret and maintain (e.g., neural networks). In this paper we introduce our approach and we demonstrate that it is a major leap forward w.r.t. previous work on the topic in several aspects: (i) it significantly decreases the number of false positives, which is orders of magnitude lower than in state-of-the-art comparable approaches (we demonstrate this using an experimental dataset consisting of millions of real enterprise transactions); (ii) it creates profiles that are easy to understand and update, and therefore it provides an explanation of the origins of an anomaly; (iii) it allows the introduction of a feedback mechanism that makes possible for the system to improve based on its own mistakes; and (iv) feature aggregation and transaction flow analysis allow the system to detect threats which span over multiple features and multiple transactions

Preliminary design criteria of Stirling engines taking into account real gas effects

The gas circuit and the drive mechanism are the main subsystems of a Stirling engine. Models can be used to study these subsystems. The numerical computing power currently available allows the development of models with fewer simplifying assumptions than was possible decades ago. Because all models must be validated experimentally, the benefit of the advanced models is not greater accuracy but the ability to analyse physical phenomena dependent on variables whose experimental measurement is practically impossible. For now, simple models are needed at the preliminary design stage, while the advanced models can be appropriate for optimisation tasks. Beale and West numbers were probably the most commonly used criteria for sizing of engines at the preliminary design stage. Without prejudice to its historical importance, it should be recognized that both concepts are experimental correlations where great simplifications have been made. So far it has hardly been highlighted that these dimensionless numbers have two important limitations, namely: (a) do not provide criteria of independent design for the gas circuit and the drive mechanism, because they refer to brake power; and (b) do not allow to accurately estimate the maximum brake power, since there is no correlation or design criteria generally accepted to estimate the speed corresponding to the maximum brake power. In previous publications, more complete preliminary design criteria have been proposed by means of dimensional analysis, considering separately the gas circuit and the drive mechanism. In this method, the concept of quasi-static simulation and characteristic Mach number are essential for dimensioning the gas circuit, while the characteristic Stirling number is important from the standpoint of mechanical efficiency. In this article we update a database that contains the main geometric parameters, operating variables and experimental results of power and efficiency corresponding to engines of different size and characteristics. The database also includes simulation results. Since recent investigations claims that a Stirling machine operating at very high pressure and moderate maximum temperature allows the realization of small engines with significant useful power, with advantages in structural problems and the seals realization, the simulations also consider operating conditions for which the working fluid may evidence real gas effects. The concept of dimensionless quasi-static indicated power introduced in previous work using the ideal gas model, is now substituted by the analogous concept that results from an equation of state for real gases. Both values are compared with the approximation derived from the model of Schmidt, in order to evaluate separately how the mechanism simplification and the equation of state affect. We analyse the ratio between the dimensionless value of the maximum indicated power (a sort of ‘indicated’ Beale number) and the procedure to estimate the maximum brake power can be completed by analysing the ratio between the dimensionless rotation frequencies at the operating points of maximum brake power and maximum indicated power, as well as the values of the mechanical efficiency at the point of maximum brake power