Transcriptional regulation of the yghJ-pppA-yghG-gspCDEFGHIJKLM cluster, encoding the type II secretion pathway in Enterotoxigenic Escherichia coli

The gene cluster gspCDEFGHIJKLM codes for various structural components of the type II secretion pathway which is responsible for the secretion of heat-labile enterotoxin by enterotoxigenic Escherichia coli (ETEC). In this work, we used a variety of molecular approaches to elucidate the transcriptional organization of the ETEC type II secretion system and to unravel the mechanisms by which the expression of these genes is controlled. We showed that the gspCDEFGHIJKLM cluster and three other upstream genes, yghJ, pppA, and yghG, are cotranscribed and that a promoter located in the upstream region of yghJ plays a major role in the expression of this 14-gene transcriptional unit. Transcription of the yghJ promoter was repressed 168-fold upon a temperature downshift from 37°C to 22°C. This temperature-induced repression was mediated by the global regulatory proteins H-NS and StpA. Deletion mutagenesis showed that the promoter region encompassing positions −321 to +301 relative to the start site of transcription of yghJ was required for full repression. The yghJ promoter region is predicted to be highly curved and bound H-NS or StpA directly. The binding of H-NS or StpA blocked transcription initiation by inhibiting promoter open complex formation. Unraveling the mechanisms of regulation of type II secretion by ETEC enhances our understanding of the pathogenesis of ETEC and other pathogenic varieties of E. coli.

The type II secretion system and its ubiquitous lipoprotein substrate, SsIE are required for biofilm formation and virulence of enteropathogenic escherichia coli

Enteropathogenic Escherichia coli (EPEC) is a major cause of diarrhea in infants in developing countries. We have identified a functional type II secretion system (T2SS) in EPEC that is homologous to the pathway responsible for the secretion of heat-labile enterotoxin by enterotoxigenic E. coli. The wild-type EPEC T2SS was able to secrete a heat-labile enterotoxin reporter, but an isogenic T2SS mutant could not. We showed that the major substrate of the T2SS in EPEC is SslE, an outer membrane lipoprotein (formerly known as YghJ), and that a functional T2SS is essential for biofilm formation by EPEC. T2SS and SslE mutants were arrested at the microcolony stage of biofilm formation, suggesting that the T2SS is involved in the development of mature biofilms and that SslE is a dominant effector of biofilm development. Moreover, the T2SS was required for virulence, as infection of rabbits with a rabbit-specific EPEC strain carrying a mutation in either the T2SS or SslE resulted in significantly reduced intestinal colonization and milder disease.

Comparing personality type profiles of primary teachers in the Catholic and state school systems

Continuous finite-time state feedback stabilizers for some nonlinear stochastic systems

This paper is concerned with the problem of finite-time stabilization for some nonlinear stochastic systems. Based on the stochastic Lyapunov theorem on finite-time stability that has been established by the authors in the paper, it is proven that Euler-type stochastic nonlinear systems can be finite-time stabilized via a family of continuous feedback controllers. Using the technique of adding a power integrator, a continuous, global state feedback controller is constructed to stabilize in finite time a large class of two-dimensional lower-triangular stochastic nonlinear systems. Also, for a class of three-dimensional lower-triangular stochastic nonlinear systems, a recursive design scheme of finite-time stabilization is given by developing the technique of adding a power integrator and constructing a continuous feedback controller. Finally, a simulation example is given to illustrate the theoretical results. © 2014 John Wiley & Sons, Ltd.

Switch point finding using polynomial regression for fuzzy type reduction algorithms

Karnik-Mendel (KM) algorithm is the most widely used type reduction (TR) method in literature for the design of interval type-2 fuzzy logic systems (IT2FLS). Its iterative nature for finding left and right switch points is its Achilles heel. Despite a decade of research, none of the alternative TR methods offer uncertainty measures equivalent to KM algorithm. This paper takes a data-driven approach to tackle the computational burden of this algorithm while keeping its key features. We propose a regression method to approximate left and right switch points found by KM algorithm. Approximator only uses the firing intervals, rnles centroids, and FLS strnctural features as inputs. Once training is done, it can precisely approximate the left and right switch points through basic vector multiplications. Comprehensive simulation results demonstrate that the approximation accuracy for a wide variety of FLSs is 100%. Flexibility, ease of implementation, and speed are other features of the proposed method.

Host defense at the ocular surface

Microbial infections of the cornea frequently cause painful, blinding and debilitating disease that is often difficult to treat and may require corneal transplantation. In addition, sterile corneal infiltrates that are associated with contact lens wear cause pain, visual impairment and photophobia. In this article, we review the role of Toll-Like Receptors (TLR) in bacterial keratitis and sterile corneal infiltrates, and describe the role of MD-2 regulation in LPS responsiveness by corneal epithelial cells. We conclude that both live bacteria and bacterial products activate Toll-Like Receptors in the cornea, which leads to chemokine production and neutrophil recruitment to the corneal stroma. While neutrophils are essential for bacterial killing, they also cause tissue damage that results in loss of corneal clarity. These disparate outcomes, therefore, represent a spectrum of disease severity based on this pathway, and further indicate that targeting the TLR pathway is a feasible approach to treating inflammation caused by live bacteria and microbial products. Further, as the P. aeruginosa type III secretion system (T3SS) also plays a critical role in disease pathogenesis by inducing neutrophil apoptosis and facilitating bacterial growth in the cornea, T3SS exotoxins are additional targets for therapy for P. aeruginosa keratitis.

Inquisition of Microcystis aeruginosa and Synechocystis nanowires: characterization and modelling

Identification of extracellular conductive pilus-like structures (PLS) i.e. microbial nanowires has spurred great interest among scientists due to their potential applications in the fields of biogeochemistry, bioelectronics, bioremediation etc. Using conductive atomic force microscopy, we identified microbial nanowires in Microcystis aeruginosa PCC 7806 which is an aerobic, photosynthetic microorganism. We also confirmed the earlier finding that Synechocystis sp. PCC 6803 produces microbial nanowires. In contrast to the use of highly instrumented continuous flow reactors for Synechocystis reported earlier, we identified simple and optimum culture conditions which allow increased production of nanowires in both test cyanobacteria. Production of these nanowires in Synechocystis and Microcystis were found to be sensitive to the availability of carbon source and light intensity. These structures seem to be proteinaceous in nature and their diameter was found to be 4.5-7 and 8.5-11 nm in Synechocystis and M. aeruginosa, respectively. Characterization of Synechocystis nanowires by transmission electron microscopy and biochemical techniques confirmed that they are type IV pili (TFP) while nanowires in M. aeruginosa were found to be similar to an unnamed protein (GenBank : CAO90693.1). Modelling studies of the Synechocystis TFP subunit i.e. PilA1 indicated that strategically placed aromatic amino acids may be involved in electron transfer through these nanowires. This study identifies PLS from Microcystis which can act as nanowires and supports the earlier hypothesis that microbial nanowires are widespread in nature and play diverse roles.

Probing synechocystis-arsenic interactions through extracellular nanowires.

Microbial nanowires (MNWs) can play an important role in the transformation and mobility of toxic metals/metalloids in environment. The potential role of MNWs in cell-arsenic (As) interactions has not been reported in microorganisms and thus we explored this interaction using Synechocystis PCC 6803 as a model system. The effect of half maximal inhibitory concentration (IC50) [~300 mM As (V) and ~4 mM As (III)] and non-inhibitory [4X lower than IC50, i.e., 75 mM As (V) and 1 mM As (III)] of As was studied on Synechocystis cells in relation to its effect on Chlorophyll (Chl) a, type IV pili (TFP)-As interaction and intracellular/extracellular presence of As. In silico analysis showed that subunit PilA1 of electrically conductive TFP, i.e., microbial nanowires of Synechocystis have putative binding sites for As. In agreement with in silico analysis, transmission electron microscopy analysis showed that As was deposited on Synechocystis nanowires at all tested concentrations. The potential of Synechocystis nanowires to immobilize As can be further enhanced and evaluated on a large scale and thus can be applied for bioremediation studies.

Design of linear functional observers for time-delay systems of the neutral-type

This paper presents the design of reduced-order linear functional observers for a class of linear time-delay systems of the neutral-type. The type of the observer proposed in this paper is without internal delay and its order is the same as the number of linear functions to be estimated. First, conditions for the existence of the reduced-order functional observers that are capable of asymptotically estimating any given function of the state vector are derived. Then, based on the newly derived existence conditions, a procedure is given for the determination of the observer parameters. The results derived in this paper include a range of linear systems and extend some existing results of linear functional observers to linear neutral delay systems. A numerical example is given to illustrate the design procedure.

International examples of large-scale systems-theory and practice IV: B2B e-commerce implementation in the Australian context

Two of the most commonly used classifications in IS research are the factor approach and the process approach. While many studies of IS implementation are undertaken using a factor approach, little research so far examines the process of e-commerce implementation, especially in relation to the implementation of e-commerce in business-to-business (B2B) relationships. A holistic understanding of implementation which combines both the factor and process approaches using a case study method, is suggested as particularly suitable because of its ability to capture the reality of e-commerce implementation in an organisation's natural environment and in much greater detail than is possible using one of these approaches alone. In this paper, therefore, we endeavour to contribute to what we perceive as a gap in the body of theory surrounding the implementation process in the business-to-business e-commerce literature. We describe the findings of multiple case studies involving ten major Australian e-commerce initiators. In addition to confirming our earlier finding of the importance of non-technical factors for the success of the implementation process we also present, through our case studies, the various management and business issues associated with the success or failure of B2B e-commerce implementation.

Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies

Background
Automated candidate gene prediction systems allow geneticists to hone in on disease genes more rapidly by identifying the most probable candidate genes linked to the disease phenotypes under investigation. Here we assessed the ability of eight different candidate gene prediction systems to predict disease genes in intervals previously associated with type 2 diabetes by benchmarking their performance against genes implicated by recent genome-wide association studies.

Results
Using a search space of 9556 genes, all but one of the systems pruned the genome in favour of genes associated with moderate to highly significant SNPs. Of the 11 genes associated with highly significant SNPs identified by the genome-wide association studies, eight were flagged as likely candidates by at least one of the prediction systems. A list of candidates produced by a previous consensus approach did not match any of the genes implicated by 706 moderate to highly significant SNPs flagged by the genome-wide association studies. We prioritized genes associated with medium significance SNPs.

Conclusion
The study appraises the relative success of several candidate gene prediction systems against independent genetic data. Even when confronted with challengingly large intervals, the candidate gene prediction systems can successfully select likely disease genes. Furthermore, they can be used to filter statistically less-well-supported genetic data to select more likely candidates. We suggest consensus approaches fail because they penalize novel predictions made from independent underlying databases. To realize their full potential further work needs to be done on prioritization and annotation of genes.

Short term load forecasting using interval type-2 fuzzy logic systems

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy may drop due to presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. This paper proposes the application of Interval Type-2 Fuzzy Logic Systems (IT2 FLSs) for the problem of STLF. IT2 FLSs, with extra degrees of freedom, are an excellent tool for handling prevailing uncertainties and improving the prediction accuracy. Experiments conducted with real datasets show that IT2 FLS models appropriately approximate future load demands with an acceptable accuracy. Furthermore, they demonstrate an encouraging degree of accuracy superior to feedforward neural networks used in this study.

Interval type-2 fuzzy logic systems for load forecasting : a comparative study

Accurate short term load forecasting (STLF) is essential for a variety of decision-making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. This paper proposes the application of Interval Type-2 Fuzzy Logic Systems (IT2 FLSs) for the problem of STLF. IT2 FLSs, with additional degrees of freedom, are an excellent tool for handling uncertainties and improving the prediction accuracy. Experiments conducted with real datasets show that IT2 FLS models precisely approximate future load demands with an acceptable accuracy. Furthermore, they demonstrate an encouraging degree of accuracy superior to feedforward neural networks and traditional type-1 Takagi-Sugeno-Kang (TSK) FLSs.

Prediction interval construction using interval type-2 fuzzy logic systems

This study proposes a novel non-parametric method for construction of prediction intervals (PIs) using interval type-2 Takagi-Sugeno-Kang fuzzy logic systems (IT2 TSK FLSs). The key idea in the proposed method is to treat the left and right end points of the type-reduced set as the lower and upper bounds of a PI. This allows us to construct PIs without making any special assumption about the data distribution. A new training algorithm is developed to satisfy conditions imposed by the associated confidence level on PIs. Proper adjustment of premise and consequent parameters of IT2 TSK FLSs is performed through the minimization of a PI-based objective function, rather than traditional error-based cost functions. This new cost function covers both validity and informativeness aspects of PIs. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Quantitative measures are applied for assessing the quality of PIs constructed using IT2 TSK FLSs. The demonstrated results for four benchmark case studies with homogenous and heterogeneous noise clearly show the proposed method is capable of generating high quality PIs useful for decision-making.