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.

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 vs. machine : identification of bat species from their echolocation calls by humans and by artificial neural networks

Automated remote ultrasound detectors allow large amounts of data on bat presence and activity to be collected. Processing of such data involves identifying bat species from their echolocation calls. Automated species identification has the potential to provide more consistent, predictable, and potentially higher levels of accuracy than identification by humans. In contrast, identification by humans permits flexibility and intelligence in identification, as well as the incorporation of features and patterns that may be difficult to quantify. We compared humans with artificial neural networks (ANNs) in their ability to classify short recordings of bat echolocation calls of variable signal to noise ratios; these sequences are typical of those obtained from remote automated recording systems that are often used in large-scale ecological studies. We presented 45 recordings (1–4 calls) produced by known species of bats to ANNs and to 26 human participants with 1 month to 23 years of experience in acoustic identification of bats. Humans correctly classified 86% of recordings to genus and 56% to species; ANNs correctly identified 92% and 62%, respectively. There was no significant difference between the performance of ANNs and that of humans, but ANNs performed better than about 75% of humans. There was little relationship between the experience of the human participants and their classification rate. However, humans with <1 year of experience performed worse than others. Currently, identification of bat echolocation calls by humans is suitable for ecological research, after careful consideration of biases. However, improvements to ANNs and the data that they are trained on may in future increase their performance to beyond those demonstrated by humans.

Identification of New Zealand bats in flight from analysis of echolocation calls by artificial neural networks.

Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

Acoustic identification of 12 species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Bacterial adherence and biofilm formation on medical implants : a review

Biofilms are a complex group of microbial cells that adhere to the exopolysaccharide matrix present on the surface of medical devices. Biofilm-associated infections in the medical devices pose a serious problem to the public health and adversely affect the function of the device. Medical implants used in oral and orthopedic surgery are fabricated using alloys such as stainless steel and titanium. The biological behavior, such as osseointegration and its antibacterial activity, essentially depends on both the chemical composition and the morphology of the surface of the device. Surface treatment of medical implants by various physical and chemical techniques are attempted in order to improve their surface properties so as to facilitate bio-integration and prevent bacterial adhesion. The potential source of infection of the surrounding tissue and antimicrobial strategies are from bacteria adherent to or in a biofilm on the implant which should prevent both biofilm formation and tissue colonization. This article provides an overview of bacterial biofilm formation and methods adopted for the inhibition of bacterial adhesion on medical implants

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.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Development of a pilot-scale bacterial fermentation for plasmid-based biopharmaceutical production using a stoichiometric medium

The recognition of the potential efficacy of plasmid DNA (pDNA) molecules as vectors in the treatment and prevention of emerging diseases has birthed the confidence to combat global pandemics. This is due to the close-to-zero safety concern associated with pDNA vectors compared to viral vectors in cell transfection and targeting. Considerable attention has been paid to the potential of pDNA vectors but comparatively less thought has been given to the practical challenges in producing large quantities to meet current rising demands. A pilot-scale fermentation scheme was developed by employing a stoichiometrically-designed growth medium whose exceptional plasmid yield performance was attested in a shake flask environment for pUC19 and pEGFP-N1 transformed into E. coliDH5α and E. coliJM109, respectively. Batch fermentation of E. coliDH5α-pUC19 employing the stoichiometric medium displayed a maximum plasmid volumetric and specific yield of 62.6 mg/L and 17.1 mg/g (mg plasmid/g dry cell weight), respectively. Fed-batch fermentation of E. coliDH5α-pUC19 on a glycerol substrate demonstrated one of the highest ever reported pilot-scale plasmid specific yield of 48.98 mg/g and a volumetric yield of 0.53 g/L. The attainment of high plasmid specific yields constitutes a decrease in plasmid manufacturing cost and enhances the effectiveness of downstream processes by reducing the proportion of intracellular impurities. The effect of step-rise temperature induction was also considered to maximize ColE1-origin plasmid replication.

Affinity purification of plasmid DNA directly from crude bacterial cell lysates

We have shown previously that a sequence-specific DNA-binding protein based on the Lac repressor protein can isolate pre-purified DNA efficiently from simple buffer solution but our attempts to purify plasmids directly from crude starting materials were disappointing with unpractically low DNA yields. We have optimized tbe procedure and present a simple affinity methodology whereby plasmid DNA is purified directly by mixing two crude cell lysates, one cell lysate containing the plasmid and the other the protein affinity ligand, without the need for treatment by RNaseA. After IMAC chromatography, high purity supercoiled DNA is recovered in good yields of 100-150 μg plasmid per 200 mL shake flask culture. Moreover, the resulting DNA is free from linear or open-circular plasmid DNA, genomic DNA, RNA, and protein, to the limits of our detection. Furthermore, we show that lyophilized affinity ligand can be stored at room temperature and re-hydrated for use when required.

The quality of life and caregiving burden among caregivers of people with dementia in Hanoi, Bac Ninh and Hai Phong, Vietnam

This three phase study aimed to describe dementia carer's quality of life (QoL) and perceived burden, and explore the associations between family carer characteristics, burden and perceived QoL in Vietnam. Dementia carers in the capital, Hanoi, in Phase 1 (N= 153) and from Hanoi, Hai Phong and Bac Ninh in Phase 2 (N=347) completed questionnaires. Survey results showed dementia carers reported low QoL, predicted by high perceived burden. Other carer characteristics including age, gender, family income and perceived experience were significantly associated with QoL. Filial piety contributed to only a single domain of QoL. Phase 3 employed qualitative methods to explore the specific issues faced by daughter carers. Findings suggested that filial gratitude and positive aspects of the role may influence the caring experience of daughter carers. Further investigation of the specific support needs of general dementia carers, and daughter carers in particular, in Vietnam is warranted.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

A conjugative plasmid carrying the carbapenem resistance gene blaOXA-23 in AbaR4 in an extensively resistant GC1 Acinetobacter baumannii isolate

OBJECTIVES: To locate the acquired bla(OXA-23) carbapenem resistance gene in an Australian A. baumannii global clone 1 (GC1) isolate. METHODS: The genome of the extensively antibiotic-resistant GC1 isolate A85 harbouring bla(OXA-23) in Tn2006 was sequenced using Illumina HiSeq, and the reads were used to generate a de novo assembly. PCR was used to assemble relevant contigs. Sequences were compared with ones in GenBank. Conjugation experiments were conducted. RESULTS: The sporadic GC1 isolate A85, recovered in 2003, was extensively resistant, exhibiting resistance to imipenem, meropenem and ticarcillin/clavulanate, to cephalosporins and fluoroquinolones and to the older antibiotics gentamicin, kanamycin and neomycin, sulfamethoxazole, trimethoprim and tetracycline. Genes for resistance to older antibiotics are in the chromosome, in an AbaR3 resistance island. A second copy of the ampC gene in Tn6168 confers cephalosporin resistance and the gyrA and parC genes have mutations leading to fluoroquinolone resistance. An 86 335 bp repAci6 plasmid, pA85-3, carrying bla(OXA-23) in Tn2006 in AbaR4, was shown to transfer imipenem, meropenem and ticarcillin/clavulanate resistance into a susceptible recipient. A85 also contains two small cryptic plasmids of 2.7 and 8.7 kb. A85 is sequence type ST126 (Oxford scheme) and carries a novel KL15 capsule locus and the OCL3 outer core locus. CONCLUSIONS: A85 represents a new GC1 lineage identified by the novel capsule locus but retains AbaR3 carrying genes for resistance to older antibiotics. Resistance to imipenem, meropenem and ticarcillin/clavulanate has been introduced into A85 by pA85-3, a repAci6 conjugative plasmid carrying Tn2006 in AbaR4.