Discovery of an archetypal protein transport system in bacterial outer membranes

Bacteria have mechanisms to export proteins for diverse purposes, including colonization of hosts and pathogenesis. A small number of archetypal bacterial secretion machines have been found in several groups of bacteria and mediate a fundamentally distinct secretion process. Perhaps erroneously, proteins called 'autotransporters' have long been thought to be one of these protein secretion systems. Mounting evidence suggests that autotransporters might be substrates to be secreted, not an autonomous transporter system. We have discovered a new translocation and assembly module (TAM) that promotes efficient secretion of autotransporters in proteobacteria. Functional analysis of the TAM in Citrobacter rodentium, Salmonella enterica and Escherichia coli showed that it consists of an Omp85-family protein, TamA, in the outer membrane and TamB in the inner membrane of diverse bacterial species. The discovery of the TAM provides a new target for the development of therapies to inhibit colonization by bacterial pathogens.

Innate transcriptional networks activated in bladder in response to uropathogenic Escherichia coli drive diverse biological pathways and rapid synthesis of IL-10 for defense against bacterial urinary tract infection

Early transcriptional activation events that occur in bladder immediately following bacterial urinary tract infection (UTI) are not well defined. In this study, we describe the whole bladder transcriptome of uropathogenic Escherichia coli (UPEC) cystitis in mice using genome-wide expression profiling to define the transcriptome of innate immune activation stemming from UPEC colonization of the bladder. Bladder RNA from female C57BL/6 mice, analyzed using 1.0 ST-Affymetrix microarrays, revealed extensive activation of diverse sets of innate immune response genes, including those that encode multiple IL-family members, receptors, metabolic regulators, MAPK activators, and lymphocyte signaling molecules. These were among 1564 genes differentially regulated at 2 h postinfection, highlighting a rapid and broad innate immune response to bladder colonization. Integrative systems-level analyses using InnateDB (http://www.innatedb.com) bioinformatics and ingenuity pathway analysis identified multiple distinct biological pathways in the bladder transcriptome with extensive involvement of lymphocyte signaling, cell cycle alterations, cytoskeletal, and metabolic changes. A key regulator of IL activity identified in the transcriptome was IL-10, which was analyzed functionally to reveal marked exacerbation of cystitis in IL-10–deficient mice. Studies of clinical UTI revealed significantly elevated urinary IL-10 in patients with UPEC cystitis, indicating a role for IL-10 in the innate response to human UTI. The whole bladder transcriptome presented in this work provides new insight into the diversity of innate factors that determine UTI on a genome-wide scale and will be valuable for further data mining. Identification of protective roles for other elements in the transcriptome will provide critical new insight into the complex cascade of events that underpin UTI.

Structure and function of DsbA, a key bacterial oxidative folding catalyst

Since its discovery in 1991, the bacterial periplasmic oxidative folding catalyst DsbA has been the focus of intense research. Early studies addressed why it is so oxidizing and how it is maintained in its less stable oxidized state. The crystal structure of Escherichia coli DsbA (EcDsbA) revealed that the oxidizing periplasmic enzyme is a distant evolutionary cousin of the reducing cytoplasmic enzyme thioredoxin. Recent significant developments have deepened our understanding of DsbA function, mechanism, and interactions: the structure of the partner membrane protein EcDsbB, including its complex with EcDsbA, proved a landmark in the field. Studies of DsbA machineries from bacteria other than E. coli K-12 have highlighted dramatic differences from the model organism, including a striking divergence in redox parameters and surface features. Several DsbA structures have provided the first clues to its interaction with substrates, and finally, evidence for a central role of DsbA in bacterial virulence has been demonstrated in a range of organisms. Here, we review current knowledge on DsbA, a bacterial periplasmic protein that introduces disulfide bonds into diverse substrate proteins and which may one day be the target of a new class of anti-virulence drugs to treat bacterial infection. Antioxid. Redox Signal. 14, 1729–1760.

DSB proteins and bacterial pathogenicity

If DNA is the information of life, then proteins are the machines of life — but they must be assembled and correctly folded to function. A key step in the protein-folding pathway is the introduction of disulphide bonds between cysteine residues in a process called oxidative protein folding. Many bacteria use an oxidative protein-folding machinery to assemble proteins that are essential for cell integrity and to produce virulence factors. Although our current knowledge of this machinery stems largely from Escherichia coli K-12, this view must now be adjusted to encompass the wider range of disulphide catalytic systems present in bacteria.

Combining passive sampling and toxicity testing for evaluation of mixtures of polar organic chemicals in sewage treatment plant effluent

Effluent from sewage treatment plants has been associated with a range of pollutant effects. Depending on the influent composition and treatment processes the effluent may contain a myriad of different chemicals which makes monitoring very complex. In this study we aimed to monitor relatively polar organic pollutant mixtures using a combination of passive sampling techniques and a set of biochemistry based assays covering acute bacterial toxicity (Microtox™), phytotoxicity (Max-I-PAM assay) and genotoxicity (umuC assay). The study showed that all of the assays were able to detect effects in the samples and allowed a comparison of the two plants as well as a comparison between the two sampling periods. Distinct improvements in water quality were observed in one of the plants as result of an upgrade to a UV disinfection system, which improved from 24× sample enrichment required to induce a 50% response in the Microtox™ assay to 84×, from 30× sample enrichment to induce a 50% reduction in photosynthetic yield to 125×, and the genotoxicity observed in the first sampling period was eliminated. Thus we propose that biochemical assay techniques in combination with time integrated passive sampling can substantially contribute to the monitoring of polar organic toxicants in STP effluents.

Enhancement of bacterial mutagenicity of bifunctional alkylating agents by expression of mammalian glutathione s-transferase

Recently, we inserted the plasmid vector pKK233-2 containing rat GSH S-transferase (GST) 5-5 cDNA into Salmonella typhimurium TA1535 and found that these bacteria [GST 5-5(+)] expressed the protein and produced mutations when ethylene or methylene dihalides were added [Thier, R., Taylor, J. B., Pemble, S. E., Ketterer, B., Persmark, M., Humphreys, W. G., and Guengerich, F. P. (1993) Proc. Natl. Acad. Sci. U.S.A. 90, 8576-8580]. After exposure to the known GST 5-5 substrate 1,2-epoxy-3-(4′-nitrophenoxy)propane, the GST 5-5(+) strain showed fewer mutants than the bacteria transfected with the cDNA clone in a reverse orientation [GST 5-5(-)], suggesting a protective role of GST 5-5. However, mutations were considerably enhanced in the GST 5-5(+) strain [as compared to GST 5-5(-)] when 1,2,3,4-diepoxybutane (butadiene diepoxide) or 1,2-epoxy-4-bromobutane was added. The GST 5-5(+) and GST 5-5(-) bacterial stains showed similar responses to 1,2-epoxypropane, 3,4-epoxy-1-butene, and 1,4-dibromobutane. The results suggest that some bifunctional activated butanes are transformed to mutagenic products through GSH conjugation. We also found that the GST 5-5(+) strain showed enhanced mutagenicity with 1,4-dibromo-2,3-epoxybutane, 1,2-epoxy-3-bromopropane (epibromohydrin), and (±)-1,4-dibromo-2,3-dihydroxybutane. The possibility was considered that a 5-membered thialonium ion may be involved in the mutagenicity. Model thialonium compounds were rather stable to hydrolysis in aqueous solution at pH 7.4 and slowly alkylated 4-(4-nitrobenzyl)pyridine. The presence of a hydroxyl group β to the sulfur did not enhance reactivity. Mechanisms involving episulfonium ions are considered more likely. Potential oxidation products of the toxic pesticide 1,2-dibromo-3-chloropropane (DBCP) were also considered in this system. DBCP itself gave rather similar results in the two strains. Others have reported that oxidation of DBCP is required for mutagenicity, along with GST-catalyzed GSH conjugation [Simula, T. P., Glancey, M. J., Söderlund, E. J., Dybing, E., and Wolf, C. R. (1993) Carcinogenesis 14, 2303-2307]. The putative oxidation product 1,2-dibromopropional did not show a difference between the two strains. However, 1,3-dichloroacetone, a model for the putative oxidation product 1-bromo-3-chloroacetone, was considerably more mutagenic in the GST 5-5(+) strain.

Human identification from video using advanced gait recognition techniques

The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Deterrence of drug driving : the impact of the ACT drug driving legislation and detection techniques

Overarching Research Questions Are ACT motorists aware of roadside saliva based drug testing operations? What is the perceived deterrent impact of the operations? What factors are predictive of future intentions to drug drive? What are the differences between key subgroups

Identifying product families using data mining techniques in manufacturing paradigm

Identifying product families has been considered as an effective way to accommodate the increasing product varieties across the diverse market niches. In this paper, we propose a novel framework to identifying product families by using a similarity measure for a common product design data BOM (Bill of Materials) based on data mining techniques such as frequent mining and clus-tering. For calculating the similarity between BOMs, a novel Extended Augmented Adjacency Matrix (EAAM) representation is introduced that consists of information not only of the content and topology but also of the fre-quent structural dependency among the various parts of a product design. These EAAM representations of BOMs are compared to calculate the similarity between products and used as a clustering input to group the product fami-lies. When applied on a real-life manufacturing data, the proposed framework outperforms a current baseline that uses orthogonal Procrustes for grouping product families.

Conformational Spread as a Mechanism for Cooperativity in the Bacterial Flagellar Switch

The bacterial flagellar switch that controls the direction of flagellar rotation during Chemotaxis has a highly cooperative response. This has previously been understood in terms of the classic two-state, concerted model of allosteric regulation. Here, we used high-resolution optical microscopy to observe switching of single motors and uncover the stochastic multistate nature of the switch. Our observations are in detailed quantitative agreement with a recent general model of allosteric cooperativity that exhibits conformational spread-the stochastic growth and shrinkage of domains of adjacent subunits sharing a particular conformational state. We expect that conformational spread will be important in explaining cooperativity in other large signaling complexes.