Culture independent analysis of greyback canegrub-associated microflora and microbial community comparison using subtractive hybridisation

Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

Cough-generated aerosols of Pseudomonas aeruginosa and other Gram Negative Bacteria from cystic fibrosis patients.

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.

Implications of faecal indicator bacteria for the microbiological assessment of roof harvested rainwater quality in Southeast Queensland, Australia

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.

A functional screen identifies lateral transfer of beta-glucuronidase (gus) from bacteria to fungi

Lateral gene transfer (LGT) from prokaryotes to microbial eukaryotes is usually detected by chance through genome-sequencing projects. Here, we explore a different, hypothesis-driven approach. We show that the fitness advantage associated with the transferred gene, typically invoked only in retrospect, can be used to design a functional screen capable of identifying postulated LGT cases. We hypothesized that beta-glucuronidase (gus) genes may be prone to LGT from bacteria to fungi (thought to lack gus) because this would enable fungi to utilize glucuronides in vertebrate urine as a carbon source. Using an enrichment procedure based on a glucose-releasing glucuronide analog (cellobiouronic acid), we isolated two gus(+) ascomycete fungi from soils (Penicillium canescens and Scopulariopsis sp.). A phylogenetic analysis suggested that their gus genes, as well as the gus genes identified in genomic sequences of the ascomycetes Aspergillus nidulans and Gibberella zeae, had been introgressed laterally from high-GC gram(+) bacteria. Two such bacteria (Arthrobacter spp.), isolated together with the gus(+) fungi, appeared to be the descendants of a bacterial donor organism from which gus had been transferred to fungi. This scenario was independently supported by similar substrate affinities of the encoded beta-glucuronidases, the absence of introns from fungal gus genes, and the similarity between the signal peptide-encoding 5' extensions of some fungal gus genes and the Arthrobacter sequences upstream of gus. Differences in the sequences of the fungal 5' extensions suggested at least two separate introgression events after the divergence of the two main Euascomycete classes. We suggest that deposition of glucuronides on soils as a result of the colonization of land by vertebrates may have favored LGT of gus from bacteria to fungi in soils.

Gene transfer to plants by diverse species of bacteria

Agrobacterium is widely considered to be the only bacterial genus capable of transferring genes to plants. When suitably modified, Agrobacterium has become the most effective vector for gene transfer in plant biotechnology1. However, the complexity of the patent landscape2 has created both real and perceived obstacles to the effective use of this technology for agricultural improvements by many public and private organizations worldwide. Here we show that several species of bacteria outside the Agrobacterium genus can be modified to mediate gene transfer to a number of diverse plants. These plant-associated symbiotic bacteria were made competent for gene transfer by acquisition of both a disarmed Ti plasmid and a suitable binary vector. This alternative to Agrobacterium-mediated technology for crop improvement, in addition to affording a versatile ‘open source’ platform for plant biotechnology, may lead to new uses of natural bacteria– plant interactions to achieve plant transformation.

Rationalizing the SER spectra of bacteria

The SER spectra of riboflavin and FAD are identical and are resonance enhanced at 514 or 532 nm. Signals from FAD/ riboflavin dominated SER spectra whenever these compounds were present with proteins or bacteria. SER spectra of very different bacteria such as Pseudomonas. aeruginosa, Bacillu. subtilis and Geobacillus. stearothermophilus were dominated by signals from FAD, even when these bacteria were added to a preformed colloid. The SERS signal of FAD is greatly reduced at 785 nm, and SER spectra of bacteria excited at 785 nm are quite different than those collected at 514 or 532 nm. This supports the assignment of the peaks in the 514 nm SER spectra of bacteria to FAD rather to amino acids or N-acetylglucosamine. The SER spectra of certain mixes of adenine and FAD showed similar changes to those of bacteria when the excitation was changed from 514/532 nm to 785 nm. The ratio of colloid: bacteria was of critical important for obtaining good SER spectra, and the addition of sodium sulfate was also beneficial. Removal of EPS from bacteria before analysis facilitated interaction with the silver surface, and may be a useful step to include in identification protocols.

Vacuum cleaner emissions as a source of indoor exposure to airborne particles and bacteria

Vacuuming can be a source of indoor exposure to biological and non-biological aerosols, although there is little data that describes the magnitude of emissions from the vacuum cleaner itself. We therefore sought to quantify emission rates of particles and bacteria from a large group of vacuum cleaners and investigate their potential determinants, including temperature, dust bags, exhaust filters, price and age. Emissions of particles between 0.009 and 20 µm and bacteria were measured from 21 vacuums. Ultrafine (<100 nm) particle emission rates ranged from 4.0 × 10^6 to 1.1 × 10^11 particles min-1. Emission of 0.54 to 20 µm particles ranged from 4.0 × 10^4 to 1.2 × 10^9 particles min-1. PM2.5 emissions were between 2.4 × 10-1 and 5.4 × 10^3 µg min-1. Bacteria emissions ranged from 0 to 7.4 × 10^5 bacteria min-1 and were poorly correlated with dust bag bacteria content and particle emissions. Large variability in emission of all parameters was observed across the 21 vacuums we assessed, which was largely not attributable to the range of determinant factors we assessed. Vacuum cleaner emissions contribute to indoor exposure to non-biological and biological aerosols when vacuuming, and this may vary markedly depending on the vacuum used.

Neutrophilic, microaerophilic Fe(II)-oxidizing bacteria are ubiquitous in aquatic habitats of a subtropical Australian coastal catchment (ubiquitous FeOB in catchment aquatic habitats)

We examined the abundance and distribution of neutrophilic, microaerophilic Fe(II)-oxidizing bacteria (FeOB) in aquatic habitats of a highly weathered, subtropical coastal catchment where Fe biogeochemistry is of environmental significance. Laboratory cultivation and microscopy indicated that stalked Gallionella and sheathed Leptothrix-like FeOB were present in microbial mats associated with a circumneutral-pH, groundwater seep and streambank surface sediment,whereas unicellular FeOB werewidespread in surface and subsurface waters, including a seep, shallow stream and estuary-adjacent groundwater. Direct Gallionella-specificPCR detected dominant bacterial members related to Sideroxydans paludicola (95% sequence identity, SI) and Gallionella capsiferriformans (96% SI) in the seep microbialmat. TGGE analysis indicated that themost common FeOB in water enrichment cultures were related to S. lithotrophicus (96% SI). The ubiquity of FeOB in Poona catchment aquatic habitats suggests bacterial Fe(II) oxidation is integral to catchment Fe biogeochemistry.

Coordinated tuning of DFIG-based wind turbines and batteries using bacteria foraging technique for maintaining constant grid power output

This paper proposes the use of battery energy storage (BES) system for the grid-connected doubly fed induction generator (DFIG). The BES would help in storing/releasing additional power in case of higher/lower wind speed to maintain constant grid power. The DC link capacitor is replaced with the BES system in a DFIG-based wind turbine to achieve the above-mentioned goal. The control scheme is modified and the co-ordinated tuning of the associated controllers to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The results from eigenvalue analysis and the time domain simulation studies are presented to elucidate the effectiveness of the BES systems in maintaining the grid stability under normal operation.

A review of the pharmacobiotic regulation of gastrointestinal inflammation by probiotics, commensal bacteria and prebiotics.

The idea that microbes induce disease has steered medical research toward the discovery of antibacterial products for the prevention and treatment of microbial infections. The twentieth century saw increasing dependency on antimicrobials as mainline therapy accentuating the notion that bacterial interactions with humans were to be avoided or desirably controlled. The last two decades, though, have seen a refocusing of thinking and research effort directed towards elucidating the critical inter-relationships between the gut microbiome and its host that control health/wellness or disease. This research has redefined the interactions between gut microbes and vertebrates, now recognizing that the microbial active cohort and its mammalian host have shared co-evolutionary metabolic interactions that span millennia. Microbial interactions in the gastrointestinal tract provide the necessary cues for the development of regulated pro- and anti-inflammatory signals that promotes immunological tolerance, metabolic regulation and other factors which may then control local and extra-intestinal inflammation. Pharmacobiotics, using nutritional and functional food additives to regulate the gut microbiome, will be an exciting growth area of therapeutics, developing alongside an increased scientific understanding of gut-microbiome symbiosis in health and disease.

Exposure to airborne fungi and bacteria in Brisbane houses after the 2011 flood

A series of flooding events occurred in Queensland, Australia during December 2010 and January 2011. The state’s capital city of Brisbane experienced major flooding in January 2011, when the Brisbane River broke its bank and inundated low lying areas.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

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.