955 resultados para Sentinel organisms
Resumo:
Microbiology is the science devoted lo the study of organisms that are too small to be seen by the naked eye. These microorganisms are a large and diverse group of free-living forms that exist as single cells or cell clusters. Being free-living, microbial cells are distinct from the cells of animals and plants as the latter are not able to live alone in nature but only in characteristic groups. A single microbial cell, generally, is able to carry out its life processes of growth, respiration and reproduction independently of other cells, either of the same kind or of different kinds. There are five subdisciplines of microbiology: (a) the study of bacteria (bacteriology); (b) the study of viruses (virology); (c) the study of algae (phycology); (d) the study of fungi (mycology); and (e) the study of protozoa (protozoology). In the examination of the environment, all five areas of microbiology are studied. This becomes obvious when discussing the significance of each of these groups of organisms in relation to human health.
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Lignocellulosic materials, such as sugar cane bagasse, a waste product of the sugarcane processing industry, agricultural residues and herbaceous crops, may serve as an abundant and comparatively cheap feedstock for largescale industrial fermentation, resulting in the production of marketable end-products. However, the complex structure of lignocellulosic materials, the presence of various hexose and pentose sugars in the hemicellulose component, and the presence of various compounds that inhibit the organisms selected for the fermentation process, all constitute barriers that add to the production costs and make full scale industrial production economically less feasible. The work presented in this thesis was conducted in order to screen microorganisms for ability to utilize pentose sugars derived from the sugar mill industrial waste. A large number of individual bacterial strains were investigated from hemi-cellulose rich material collected at the Proserpine and Maryborough sugar mills, notably soil samples from the mill sites. The research conducted to isolation of six pentose-capable Gram-positive organisms from the actinomycetes group by using pentose as a sole carbon source in the cultivation process. The isolates were identified as Corynebacterium glutamicum, Actinomyces odontolyticus, Nocardia elegans, and Propionibacterium freudenreichii all of which were isolated from the hemicellulose-enriched soil. Pentose degrading microbes are very rare in the environment, so this was a significant discovery. Previous research indicated that microbes could degrade pentose after genetic modification but the microbes discovered in this research were able to naturally utilize pentose. Six isolates, identified as four different genera, were investigated for their ability to utilize single sugars as substrates (glucose, xylose, arabinose or ribose), and also dual sugars as substrates (a hexose plus a pentose). The results demonstrated that C. glutamicum, A. odontolyticus, N. elegans, and P. freudenreichii were pentose-capable (able to grow using xylose or other pentose sugar), and also showed diauxie growth characteristics during the dual-sugar (glucose, in combination with xylose, arabinose or ribose) carbon source tests. In addition, it was shown that the isolates displayed very small differences in growth rates when grown on dual sugars as compared to single sugars, whether pentose or hexose in nature. The anabolic characteristics of C. glutamicum, A. odontolyticus, N. elegans and P. freudenreichii were subsequently investigated by qualitative analysis of their end-products, using high performance liquid chromatography (HPLC). All of the organisms produced arginine and cysteine after utilization of the pentose substrates alone. In addition, P. freudenreichii produced alanine and glycine. The end-product profile arising from culture with dual carbon sources was also tested. Interestingly, this time the product was different. All of them produced the amino acid glycine, when grown on a combination substrate-mix of glucose with xylose, and also glucose with arabinose. Only N. elegans was able to break down ribose, either singly or in combination with glucose, and the end-product of metabolism of the glucose plus ribose substrate combination was glutamic acid. The ecological analysis of microbial abundance in sugar mill waste was performed using denaturing gradient gel electrophoresis (DGGE) and also the metagenomic microarray PhyloChip method. Eleven solid samples and seven liquid samples were investigated. A very complex bacterial ecosystem was demonstrated in the seven liquid samples after testing with the PhyloChip method. It was also shown that bagasse leachate was the most different, compared to all of the other samples, by virtue of its richness in variety of taxa and the complexity of its bacterial community. The bacterial community in solid samples from Proserpine, Mackay and Maryborough sugar mills showed huge diversity. The information found from 16S rDNA sequencing results was that the bacterial genera Brevibacillus, Rhodospirillaceae, Bacillus, Vibrio and Pseudomonas were present in greatest abundance. In addition, Corynebacterium was also found in the soil samples. The metagenomic studies of the sugar mill samples demonstrate two important outcomes: firstly that the bagasse leachate, as potentially the most pentose-rich sample tested, had the most complex and diverse bacterial community; and secondly that the pentose-capable isolates that were initially discovered at the beginning of this study, were not amongst the most abundant taxonomic groups discovered in the sugar mill samples, and in fact were, as suspected, very rare. As a bioprospecting exercise, therefore, the study has discovered organisms that are naturally present, but in very small numbers, in the appropriate natural environment. This has implications for the industrial application of E-PUB, in that a seeding process using a starter culture will be necessary for industrial purposes, rather than simply assuming that natural fermentation might occur.
Resumo:
Objective: To examine the effects of extremely cold and hot temperatures on ischaemic heart disease (IHD) mortality in five cities (Beijing, Tianjin, Shanghai, Wuhan and Guangzhou) in China; and to examine the time relationships between cold and hot temperatures and IHD mortality for each city. Design: A negative binomial regression model combined with a distributed lag non-linear model was used to examine city-specific temperature effects on IHD mortality up to 20 lag days. A meta-analysis was used to pool the cold effects and hot effects across the five cities. Patients: 16 559 IHD deaths were monitored by a sentinel surveillance system in five cities during 2004–2008. Results: The relationships between temperature and IHD mortality were non-linear in all five cities. The minimum-mortality temperatures in northern cities were lower than in southern cities. In Beijing, Tianjin and Guangzhou, the effects of extremely cold temperatures were delayed, while Shanghai and Wuhan had immediate cold effects. The effects of extremely hot temperatures appeared immediately in all the cities except Wuhan. Meta-analysis showed that IHD mortality increased 48% at the 1st percentile of temperature (extremely cold temperature) compared with the 10th percentile, while IHD mortality increased 18% at the 99th percentile of temperature (extremely hot temperature) compared with the 90th percentile. Conclusions: Results indicate that both extremely cold and hot temperatures increase IHD mortality in China. Each city has its characteristics of heat effects on IHD mortality. The policy for response to climate change should consider local climate–IHD mortality relationships.
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Biological systems involving proliferation, migration and death are observed across all scales. For example, they govern cellular processes such as wound-healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behaviour. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pair-wise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplication, in the form of a partial differential equation description for the evolution of pair-wise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behaviour in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before, and our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.
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Objective: Effective management of multi-resistant organisms is an important issue for hospitals both in Australia and overseas. This study investigates the utility of using Bayesian Network (BN) analysis to examine relationships between risk factors and colonization with Vancomycin Resistant Enterococcus (VRE). Design: Bayesian Network Analysis was performed using infection control data collected over a period of 36 months (2008-2010). Setting: Princess Alexandra Hospital (PAH), Brisbane. Outcome of interest: Number of new VRE Isolates Methods: A BN is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). BN enables multiple interacting agents to be studied simultaneously. The initial BN model was constructed based on the infectious disease physician‟s expert knowledge and current literature. Continuous variables were dichotomised by using third quartile values of year 2008 data. BN was used to examine the probabilistic relationships between VRE isolates and risk factors; and to establish which factors were associated with an increased probability of a high number of VRE isolates. Software: Netica (version 4.16). Results: Preliminary analysis revealed that VRE transmission and VRE prevalence were the most influential factors in predicting a high number of VRE isolates. Interestingly, several factors (hand hygiene and cleaning) known through literature to be associated with VRE prevalence, did not appear to be as influential as expected in this BN model. Conclusions: This preliminary work has shown that Bayesian Network Analysis is a useful tool in examining clinical infection prevention issues, where there is often a web of factors that influence outcomes. This BN model can be restructured easily enabling various combinations of agents to be studied.
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BACKGROUND: The treatment for deep surgical site infection (SSI) following primary total hip arthroplasty (THA) varies internationally and it is at present unclear which treatment approaches are used in Australia. The aim of this study is to identify current treatment approaches in Queensland, Australia, show success rates and quantify the costs of different treatments. METHODS: Data for patients undergoing primary THA and treatment for infection between January 2006 and December 2009 in Queensland hospitals were extracted from routinely used hospital databases. Records were linked with pathology information to confirm positive organisms. Diagnosis and treatment of infection was determined using ICD-10-AM and ACHI codes, respectively. Treatment costs were estimated based on AR-DRG cost accounting codes assigned to each patient hospital episode. RESULTS: A total of n=114 patients with deep surgical site infection were identified. The majority of patients (74%) were first treated with debridement, antibiotics and implant retention (DAIR), which was successful in eradicating the infection in 60.3% of patients with an average cost of $13,187. The remaining first treatments were 1-stage revision, successful in 89.7% with average costs of $27,006, and 2-stage revisions, successful in 92.9% of cases with average costs of $42,772. Multiple treatments following 'failed DAIR' cost on average $29,560, for failed 1-stage revision were $24,357, for failed 2-stage revision were $70,381 and were $23,805 for excision arthroplasty. CONCLUSIONS: As treatment costs in Australia are high primary prevention is important and the economics of competing treatment choices should be carefully considered. These currently vary greatly across international settings.
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We introduce the use of Ingenuity Pathway Analysis to analyzing global metabonomics in order to characterize phenotypically biochemical perturbations and the potential mechanisms of the gentamicin-induced toxicity in multiple organs. A single dose of gentamicin was administered to Sprague Dawley rats (200 mg/kg, n = 6) and urine samples were collected at -24-0 h pre-dosage, 0-24, 24-48, 48-72 and 72-96 h post-dosage of gentamicin. The urine metabonomics analysis was performed by UPLC/MS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition analyses (Heatmap, PCA and PLS-DA), revealing a time-dependency of the biochemical perturbations induced by gentamicin toxicity. As result, the holistic metabolome change induced by gentamicin toxicity in the animal's organisms was characterized. Several metabolites involved in amino acid metabolism were identified in urine, and it was confirmed that gentamicin biochemical perturbations can be foreseen from these biomarkers. Notoriously, it was found that gentamicin induced toxicity in multiple organs system in the laboratory rats. The proof-of-knowledge based Ingenuity Pathway Analysis revealed gentamicin induced liver and heart toxicity, along with the previously known toxicity in kidney. The metabolites creatine, nicotinic acid, prostaglandin E2, and cholic acid were identified and validated as phenotypic biomarkers of gentamicin induced toxicity. Altogether, the significance of the use of metabonomics analyses in the assessment of drug toxicity is highlighted once more; furthermore, this work demonstrated the powerful predictive potential of the Ingenuity Pathway Analysis to study of drug toxicity and its valuable complementation for metabonomics based assessment of the drug toxicity.
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Interferon gamma (IFNγ) is a key Th1 cytokine, with a principal role in the immune response against intracellular organisms such as Chlamydia. Along with being responsible for significant morbidity in human populations, Chlamydia is also responsible for wide spread infection and disease in many animal hosts, with reports that many Australian koala subpopulations are endemically infected. An understanding of the role played by IFNγ in koala chlamydial diseases is important for the establishment of better prophylactic and therapeutic approaches against chlamydial infection in this host. A limited number of IFNγ sequences have been published from marsupials and no immune reagents to measure expression have been developed. Through preliminary analysis of the koala transcriptome, we have identified the full coding sequence of the koala IFNγ gene. Transcripts were identified in spleen and lymph node tissue samples. Phylogenetic analysis demonstrated that koala IFNγ is closely related to other marsupial IFNγ sequences and more distantly related to eutherian mammals. To begin to characterise the role of this important cytokine in the koala's response to chlamydial infection, we developed a quantitative real time PCR assay and applied it to a small cohort of koalas with and without active chlamydial disease, revealing significant differences in expression patterns between the groups. Description of the IFNγ sequence from the koala will not only assist in understanding this species' response to its most important pathogen but will also provide further insight into the evolution of the marsupial immune system
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Global aquaculture has expanded rapidly to address the increasing demand for aquatic protein needs and an uncertain future for wild fisheries. To date, however, most farmed aquatic stocks are essentially wild and little is known about their genomes or the genes that affect important economic traits in culture. Biologists have recognized that recent technological advances including next generation sequencing (NGS) have opened up the possibility of generating genome wide sequence data sets rapidly from non-model organisms at a reasonable cost. In an era when virtually any study organism can 'go genomic', understanding gene function and genetic effects on expressed quantitative trait locus phenotypes will be fundamental to future knowledge development. Many factors can influence the individual growth rate in target species but of particular importance in agriculture and aquaculture will be the identification and characterization of the specific gene loci that contribute important phenotypic variation to growth because the information can be applied to speed up genetic improvement programmes and to increase productivity via marker-assisted selection (MAS). While currently there is only limited genomic information available for any crustacean species, a number of putative candidate genes have been identified or implicated in growth and muscle development in some species. In an effort to stimulate increased research on the identification of growth-related genes in crustacean species, here we review the available information on: (i) associations between genes and growth reported in crustaceans, (ii) growth-related genes involved with moulting, (iii) muscle development and degradation genes involved in moulting, and; (iv) correlations between DNA sequences that have confirmed growth trait effects in farmed animal species used in terrestrial agriculture and related sequences in crustacean species. The information in concert can provide a foundation for increasing the rate at which knowledge about key genes affecting growth traits in crustacean species is gained.
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Instances of parallel ecotypic divergence where adaptation to similar conditions repeatedly cause similar phenotypic changes in closely related organisms are useful for studying the role of ecological selection in speciation. Here we used a combination of traditional and next generation genotyping techniques to test for the parallel divergence of plants from the Senecio lautus complex, a phenotypically variable groundsel that has adapted to disparate environments in the South Pacific. Phylogenetic analysis of a broad selection of Senecio species showed that members of the S. lautus complex form a distinct lineage that has diversified recently in Australasia. An inspection of thousands of polymorphisms in the genome of 27 natural populations from the S. lautus complex in Australia revealed a signal of strong genetic structure independent of habitat and phenotype. Additionally, genetic differentiation between populations was correlated with the geographical distance separating them, and the genetic diversity of populations strongly depended on geographical location. Importantly, coastal forms appeared in several independent phylogenetic clades, a pattern that is consistent with the parallel evolution of these forms. Analyses of the patterns of genomic differentiation between populations further revealed that adjacent populations displayed greater genomic heterogeneity than allopatric populations and are differentiated according to variation in soil composition. These results are consistent with a process of parallel ecotypic divergence in face of gene flow.
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Prior to the completion of the human genome project, the human genome was thought to have a greater number of genes as it seemed structurally and functionally more complex than other simpler organisms. This along with the belief of “one gene, one protein”, were demonstrated to be incorrect. The inequality in the ratio of gene to protein formation gave rise to the theory of alternative splicing (AS). AS is a mechanism by which one gene gives rise to multiple protein products. Numerous databases and online bioinformatic tools are available for the detection and analysis of AS. Bioinformatics provides an important approach to study mRNA and protein diversity by various tools such as expressed sequence tag (EST) sequences obtained from completely processed mRNA. Microarrays and deep sequencing approaches also aid in the detection of splicing events. Initially it was postulated that AS occurred only in about 5%; of all genes but was later found to be more abundant. Using bioinformatic approaches, the level of AS in human genes was found to be fairly high with 35-59%; of genes having at least one AS form. Our ability to determine and predict AS is important as disorders in splicing patterns may lead to abnormal splice variants resulting in genetic diseases. In addition, the diversity of proteins produced by AS poses a challenge for successful drug discovery and therefore a greater understanding of AS would be beneficial.
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This thesis documented pathogenic species of nontuberculous mycobacteria in the Brisbane water distribution system. When water and shower aerosol strains were compared with human strains of mycobacteria, the study found that the likelihood of acquiring infection from municipal water was specific for four main species. The method for isolation of mycobacteria from water was refined, followed by sampling from 220 sites across Brisbane. A variety of species (incl 15 pathogens) were identified and genotypically compared to human strains. For M. abscessus and M. lentiflavum, water strains clustered with human strains. Pathogenic strains of M. kansasii were found, though non-pathogenic strains dominated. Waterborne strains of M. fortuitum differed to human strains. Extensive home sampling of 20 patients with NTM disease, supported the theory that the risk of acquiring NTM from water or shower aerosols appears species specific for M. avium, M. kansasii, M. lentiflavum and M. abscessus.
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Coordinative couplings are commonly classified as interpersonal and intrapersonal. Interpersonal coordination is normally thought of as between organisms but a subset can also be considered where the co-actors movements are coupled to an environmental rhythm. This can be termed extrapersonal coordination. This study explores how coordination is achieved in a situation that demands that at least one actor makes use of extrapersonal sources. In this case multi-seat rowing, where one actor cannot see the other one behind them. A qualitative approach using experiential knowledge from expert rowers (N=9) and coaches (N=4) was used to examine how interpersonal coordination was achieved and maintained in 2 person rowing boats. It was reported that where possible, both rowers coordinated their movements by coupling with an invariant provided by the boat. This invariant is underpinned by perception of water flow past the boat; which is in turn used to determine changes in acceleration - 'rowing with the boat.' Bow seat also identified the rower in front and stroke seat identified the looming of the stern as viable alternative sources for coupling.
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The nucleotide sequences of several animal, plant and bacterial genomes are now known, but the functions of many of the proteins that they are predicted to encode remain unclear. RNA interference is a gene-silencing technology that is being used successfully to investigate gene function in several organisms - for example, Caenorhabditis elegans. We discuss here that RNA-induced gene silencing approaches are also likely to be effective for investigating plant gene function in a high-throughput, genome-wide manner.
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Most multicellular organisms regulate developmental transitions by microRNAs, which are generated by an enzyme, Dicer. Insects and fungi have two Dicer-like genes, and many animals have only one, yet the plant, Arabidopsis, has four. Examining the poplar and rice genomes revealed that they contain five and six Dicer-like genes, respectively. Analysis of these genes suggests that plants require a basic set of four Dicer types which were present before the divergence of mono- and dicotyledonous plants (∼200 million years ago), but after the divergence of plants from green algae. A fifth type of Dicer seems to have evolved in monocots. © 2006 Federation of European Biochemical Societies.