43 resultados para Pathogenic bacteria.

em Queensland University of Technology - ePrints Archive


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Proteases with important roles for bacterial pathogens which specifically reside within intracellular vacuoles are frequently homologous to those which have important virulence functions for other bacteria. Research has identified that some of these conserved proteases have evolved specialised functions for intracellular vacuole residing bacteria. Unique proteases with pathogenic functions have also been described from Chlamydia, Mycobacteria, and Legionella. These findings suggest that there are further novel functions for proteases from these bacteria which remain to be described. This review summarises recent findings of novel protease functions from the intracellular human pathogenic bacteria which reside exclusively in vacuoles.

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Surface-enhanced Raman spectroscopy (SERS) is a potentially important tool in the rapid and accurate detection of pathogenic bacteria in biological fluids. However, for diagnostic application of this technique, it is necessary to develop a highly sensitive, stable, biocompatible and reproducible SERS-active substrate. In this work, we have developed a silver–gold bimetallic SERS surface by a simple potentiostatic electrodeposition of a thin gold layer on an electrochemically roughened nanoscopic silver substrate. The resultant substrate was very stable under atmospheric conditions and exhibited the strong Raman enhancement with the high reproducibility of the recorded SERS spectra of bacteria (E. coli, S. enterica, S. epidermidis, and B. megaterium). The coating of the antibiotic over the SERS substrate selectively captured bacteria from blood samples and also increased the Raman signal in contrast to the bare surface. Finally, we have utilized the antibiotic-coated hybrid surface to selectively identify different pathogenic bacteria, namely E. coli, S. enterica and S. epidermidis from blood samples.

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Staphylococci are important pathogenic bacteria responsible for a range of diseases in humans. The most frequently isolated microorganisms in a hospital microbiology laboratory are staphylococci. The general classification of staphylococci divides them into two major groups; Coagulase-positive staphylococci (e.g. Staphylococcus aureus) and Coagulase-negative staphylococci (e.g. Staphylococcus epidermidis). Coagulase-negative staphylococcal (CoNS) isolates include a variety of species and many different strains but are often dominated by the most important organism of this group, S. epidermidis. Currently, these organisms are regarded as important pathogenic organisms causing infections related to prosthetic materials and surgical wounds. A significant number of S. epidermidis isolates are also resistant to different antimicrobial agents. Virulence factors in CoNS are not very clearly established and not well documented. S. epidermidis is evolving as a resistant and powerful microbe related to nosocomial infections because it has different properties which independently, and in combination, make it a successful infectious agent, especially in the hospital environment. Such characteristics include biofilm formation, drug resistance and the evolution of genetic variables. The purpose of this project was to develop a novel SNP genotyping method to genotype S. epidermidis strains originating from hospital patients and healthy individuals. High-Resolution Melt Analysis was used to assign binary typing profiles to both clinical and commensal strains using a new bioinformatics approach. The presence of antibiotic resistance genes and biofilm coding genes were also interrogated in these isolates.

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Staphylococcus aureus, one of the major pathogenic bacteria, is associated with substantial morbidity and mortality. The disease burden of staphylococcal infections is significant, which is primarily attributed to its adaptability and resistance to environmental stresses. S. aureus has the ability to develop multiple resistances to antimicrobial agents. These high resistances make pathogenicity of S. aureus one of the most complex mechanisms to understand and manage. Proteomic and bioinformatics approaches show great potential in exploring microbial adaptation strategies, ability to cause disease by pathogenic bacteria and the development of diagnostic tools. A summary of the latest developments in the application of ‘omics’ technologies to understand resistance mechanisms in S. aureus and their future role in antistaphylococcal vaccine and/or drug discovery is given here.

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This research investigated the microbial air quality of flooded houses in Brisbane suburbs following the January 2011 flood event. Flood waters can carry and spread human pathogenic bacteria, and these organisms can be dispersed into residential air by aerosolisation. This study found that the bacterial load was significantly different for indoor and outdoor areas of flood affected houses, but no significant differences were observed between flooded and non-flooded houses. This could be due to the rapid clean-up of flooded houses following the event. Molecular methods were used to identify and characterise staphylococcal species in residential air of flooded and non-flooded houses. A major finding was the diverse population of airborne staphylococci as well as the high rate of methicillin-resistance in these strains. By determining the genetic relatedness of residential air sourced staphylococci, a potential source for pathogenic strains can be identified.

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Cold atmospheric pressure plasma (APP) is a recent, cutting-edge antimicrobial treatment. It has the potential to be used as an alternative to traditional treatments such as antibiotics and as a promoter of wound healing, making it a promising tool in a range of biomedical applications with particular importance for combating infections. A number of studies show very promising results for APP-mediated killing of bacteria, including removal of biofilms of pathogenic bacteria such as Pseudomonas aeruginosa. However, the mode of action of APP and the resulting bacterial response are not fully understood. Use of a variety of different plasma-generating devices, different types of plasma gases and different treatment modes makes it challenging to show reproducibility and transferability of results. This review considers some important studies in which APP was used as an antibacterial agent, and specifically those that elucidate its mode of action, with the aim of identifying common bacterial responses to APP exposure. The review has a particular emphasis on mechanisms of interactions of bacterial biofilms with APP.

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Pathogens require protein-folding enzymes to produce functional virulence determinants. These foldases include the Dsb family of proteins, which catalyze oxidative folding in bacteria. Bacterial disulfide catalytic processes have been well characterized in Escherichia coli K-12 and these mechanisms have been extrapolated to other organisms. However, recent research indicates that the K-12 complement of Dsb proteins is not common to all bacteria. Importantly, many pathogenic bacteria have an extended arsenal of Dsb catalysts that is linked to their virulence. To help to elucidate the process of oxidative folding in pathogens containing a wide repertoire of Dsb proteins, Salmonella enterica serovar Typhimurium has been focused on. This Gram-negative bacterium contains three DsbA proteins: SeDsbA, SeDsbL and SeSrgA. Here, the expression, purification, crystallization and preliminary diffraction analysis of these three proteins are reported. SeDsbA, SeDsbL and SeSrgA crystals diffracted to resolution limits of 1.55, 1.57 and 2.6 Å and belonged to space groups P21, P21212 and C2, respectively.

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Pathogenic bacteria have a large repertoire of surface organelles involved in adherence, motility and protein export, but how individual bacteria co-ordinate surface organelle expression to prevent interference and excessive immune stimulation is unclear. Phase variation is a mechanism by which expression of surface factors is limited to a fraction of the bacterial population; however, the presence of multiple homologous surface structures controlled by related mechanisms and regulators antagonizes the independent expression achieved by phase variation. To investigate whether other mechanisms have evolved to sort out the bacterial cell surface, we examined regulatory cross-talk between multiple phase-variable pyelonephritis-associated pili (pap) operons in Escherichia coli isolates associated with urinary tract infections. Allelic variation identified in the regulatory regions and regulators acts synergistically to limit coexpression of homologous fimbrial operons. In particular, there is evidence that papI is under positive selection and PapI variants displayed differences in their capacity to activate related pap operons. Alleles of the high-affinity binding site for PapB were shown to contain a variable number of (T/A)3 repeats occurring every 9 bp that altered the sensitivity of pap operon activation. Taken together with other examples of surface organelle cross-talk, we illustrate how this regulation could promote sequential expression.

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Recently, a growing amount of attention has been focused on the utility of biosensors for biomedical applications. Combined with nanomaterials and nanostructures, nano-scaled biosensors are installed for biomedical applications, such as pathogenic bacteria monitoring, virus recognition, disease biomarker detection, among others. These nano-biosensors offer a number of advantages and in many respects are ideally suited to biomedical applications, which could be made as extremely flexible devices, allowing biomedical analysis with speediness, excellent selectivity and high sensitivity. This minireview discusses the literature published in the latest years on the advances in biomedical applications of nano-scaled biosensors for disease bio-marking and detection, especially in bio-imaging and the diagnosis of pathological cells and viruses, monitoring pathogenic bacteria, thus providing insight into the future prospects of biosensors in relevant clinical applications.

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Despite many synthetic biomaterials having physical properties that are comparable or even superior to those of natural body tissues, they frequently fail due to the adverse physiological reactions they cause within the human body, such as infection and inflammation. The surface modification of biomaterials is an economical and effective method by which biocompatibility and biofunctionality can be achieved while preserving the favorable bulk characteristics of the biomaterial, such as strength and inertness. Amongst the numerous surface modification techniques available, plasma surface modification affords device manufacturers a flexible and environmentally friendly process that enables tailoring of the surface morphology, structure, composition, and properties of the material to a specific need. There are a vast range of possible applications of plasma modification in biomaterial applications, however, the focus of this review paper is on processes that can be used to develop surface morphologies and chemical structures for the prevention of adhesion and proliferation of pathogenic bacteria on the surfaces of in-dwelling medical devices. As such, the fundamental principles of bacterial cell attachment and biofilm formation are also discussed. Functional organic plasma polymerised coatings are also discussed for their potential as biosensitive interfaces, connecting inorganic/metallic electronic devices with their physiological environments.

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The study aimed to evaluate the suitability of Escherichia coli, enterococci and C. perfringens to assess the microbiological quality of roof harvested rainwater, and to assess whether the concentrations of these faecal indicators can be used to predict the presence or absence of specific zoonotic bacterial or protozoan pathogens. From a total of 100 samples tested, respectively 58%, 83% and 46% of samples were found to be positive for E. coli, enterococci and C. perfringens spores, as determined by traditional culture based methods. Additionally, in the samples tested, 7%, 19%, 1%, 8%, 17%, and 15% were PCR positive for A. hydrophila lip, C. coli ceuE, C. jejuni mapA, L. pneumophila mip, Salmonella invA, and G. lamblia β-giardin genes. However, none of the samples was positive for E. coli O157 LPS, VT1, VT2 and C. parvum COWP genes. The presence or absence of these potential pathogens did not correlate with any of the faecal indicator bacterial concentrations as determined by a binary logistic regression model. The roof-harvested rainwater samples tested in this study appear to be of poor microbiological quality and no significant correlation was found between the concentration of faecal indicators and pathogenic microorganisms. The use of faecal indicator bacteria raises questions regarding their reliability in assessing the microbiological quality of water and particularly their poor correlation with pathogenic microorganisms. The presence of one or more zoonotic pathogens suggests that the microbiological analysis of water should be performed, and appropriate treatment measures should be undertaken especially in tanks where the water is used for drinking.

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Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

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Sewage and its microbiology, treatment and disposal are important to the topic of Antarctic wildlife health because disposal of untreated sewage effluent into the Antarctic marine environment is both allowed and commonplace. Human sewage contains enteric bacteria as normal flora, and has the potential to contain parasites, bacteria and viruses which may prove pathogenic to Antarctic wildlife. Treatment can reduce levels of micro-organisms in sewage effluent, but is not a requirement of the Environmental Protocol to the Antarctic Treaty (the Madrid Protocol). In contrast, the deliberate release of non-native organisms for any other reason is prohibited. Hence, disposal of sewage effluent to the marine environment is the only activity routinely undertaken in Antarctica knowing that it will likely result in the release of large numbers of potentially non-native species. When the Madrid Protocol was negotiated, the decision to allow release of untreated sewage effluent was considered the only pragmatic option, as a prohibition would have been costly, and may not have been achievable by many Antarctic operators. In addition, at that time the potential for transmission of pathogens to wildlife from sewage was not emphasised as a significant potential risk. Since then, the transmission of disease-causing agents between species is more widely recognised and it is now timely to consider the risks of continued discharge of sewage effluent in Antarctica and whether there are practical alternatives.

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Background: Pseudomonas aeruginosa is the most common bacterial pathogen in cystic fibrosis (CF) patients. Current infection control guidelines aim to prevent transmission via contact and respiratory droplet routes and do not consider the possibility of airborne transmission. We hypothesized that with coughing, CF subjects produce viable, respirable bacterial aerosols. Methods: Cross-sectional study of 15 children and 13 adults with CF, 26 chronically infected with P. aeruginosa. A cough aerosol sampling system enabled fractioning of respiratory particles of different size, and culture of viable Gram negative non-fermentative bacteria. We collected cough aerosols during 5 minutes voluntary coughing and during a sputum induction procedure when tolerated. Standardized quantitative culture and genotyping techniques were used. Results: P. aeruginosa was isolated in cough aerosols of 25 (89%) subjects of whom 22 produced sputum samples. P. aeruginosa from sputum and paired cough aerosols were indistinguishable by molecular typing. In 4 cases the same genotype was isolated from ambient room air. Approximately 70% of viable aerosols collected during voluntary coughing were of particles ≤ 3.3 microns aerodynamic diameter. P. aeruginosa, Burkholderia cenocepacia Stenotrophomonas maltophilia and Achromobacter xylosoxidans were cultivated from respiratory particles in this size range. Positive room air samples were associated with high total counts in cough aerosols (P=0.003). The magnitude of cough aerosols were associated with higher FEV1 (r=0.45, P=0.02) and higher quantitative sputum culture results (r=0.58, P=0.008). Conclusion: During coughing, CF patients produce viable aerosols of P. aeruginosa and other Gram negative bacteria of respirable size range, suggesting the potential for airborne transmission.