17 resultados para Bacterial genomes - Analysis

em Aston University Research Archive


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The analysis of bacterial genomes for epidemiological purposes often results in the production of a banding profile of DNA fragments characteristic of the genome under investigation. These may be produced using various methods, many of which involve the cutting or amplification of DNA into defined and reproducible characteristic fragments. It is frequently of interest to enquire whether the bacterial isolates are naturally classifiable into distinct groups based on their DNA profiles. A major problem with this approach is whether classification or clustering of the data is even appropriate. It is always possible to classify such data but it does not follow that the strains they represent are ‘actually’ classifiable into well-defined separate parts. Hence, the act of classification does not in itself answer the question: do the strains consist of a number of different distinct groups or species or do they merge imperceptibly into one another because DNA profiles vary continuously? Nevertheless, we may still wish to classify the data for ‘convenience’ even though strains may vary continuously, and such a classification has been called a ‘dissection’. This Statnote discusses the use of classificatory methods in analyzing the DNA profiles from a sample of bacterial isolates.

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The application of mechanical insults to the spinal cord results in profound cellular and molecular changes, including the induction of neuronal cell death and altered gene expression profiles. Previous studies have described alterations in gene expression following spinal cord injury, but the specificity of this response to mechanical stimuli is difficult to investigate in vivo. Therefore, we have investigated the effect of cyclic tensile stresses on cultured spinal cord cells from E15 Sprague-Dawley rats, using the FX3000 Flexercell Strain Unit. We examined cell morphology and viability over a 72 hour time course. Microarray analysis of gene expression was performed using the Affymetrix GeneChip System, where categorization of identified genes was performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) systems. Changes in expression of 12 genes were validated with quantitative real-time reverse transcription polymerase chain reaction (RT-PCR).

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Aeromonas genomes were investigated by restriction digesting chromosomal DNA with the endonuclease XbaI, separation of restriction fragments by pulsed field gel electrophoresis (PFGE) and principal components analysis (PCA) of resulting separation patterns. A. salmonicida salmonicida were unique amongst the isolates investigated. Separation profiles of these isolates were similar and all characterised by a distinct absence of bands in the 250kb region. Principal components analysis represented these strains as a clearly defined homogeneous group separated by insignificant Euclidian distances. However, A. salmonicida achromogenes isolates in common with those of A. hydrophila and A. sobria were shown by principal components analysis to be more heterogeneous in nature. Fragments from these isolates were more uniform in size distribution but as demonstrated by the Euclidian distances attained through PCA potentially characteristic of each strain. Furthermore passaging of Aeromonas isolates through an appropriate host did not greatly modify fragment separation profiles, indicative of the genomic stability of test aeromonads and the potential of restriction digesting/PFGE/PCA in Aeromonas typing.

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Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences that bind across more than one HLA allele with high affinity (IC50 <50nM). The reliability of software programmes used, polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.

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Rainbow trout eggs Salmo gairdneri, Richardson, were incubated under a range of different environmental conditions. Recovery of bacteria from egg surfaces revealed that increased water temperature, slow water flow rates and high egg density all significantly increased egg surface bacterial populations. Live eggs were mainly colonized by Cytophaga sp., pseudomonas fluorescens and Aeromonas hydrophila. In contrast, dead eggs supported considerable numbers of fluorescent Pseudomonas sp. Analysis of potential nutrient sources for bacteria colonizing live egg surfaces revealed that small amounts of amino acids, phosphate and potassium may be lost by incubating eggs. Subsequently these nutrients were shown to be capable of supporting limited bacterial growth and reproduction. Dead eggs `leaked' increased amounts of the above nutrients which in turn supported higher bacterial numbers. In addition, biochemical analysis of eggs revealed amino acids and fatty acids that might be utilized by bacteria colonizing dead egg surfaces. Assessment of adhesion properties of bacteria frequently recovered from egg surfaces revealed high cell surface hydrophobicity as an important factor in successful egg colonization. Analysis of egg mortalities from groups of rainbow trout and brown trout (S.trutta L.) eggs maintained under two different incubation systems revealed that potentially a close correlation existed between egg surface bacterial numbers and mortalities in the egg during incubation. Innoculation of newly-fertilized eggs with bacteria demonstrated that groups of eggs supporting high numbers of P.fluorescens suffered significantly higher mortalities during the early part of their incubation. Exposure of incubating eggs to oxolinic acid, chlortetracycline and chloramphenicol demonstrated that numbers of bacteria on egg surfaces could be significantly reduced. However, as no corresponding increase in egg hatching success was revealed, the treatment of incubating eggs with antibiotics or antimicrobial compounds can not be recommended. In commercial hatcheries bacteria are only likely to be responsible for egg deaths during incubation when environmental conditions are unfavourable. High water temperatures, slow water flow rates and high egg density all lead to increased bacterial number of egg surfaces, reduced water circulation and low levels of dissolved oxygen. Under such circumstances sufficient amounts of dissolved oxygen may not be available to support developing embryos.

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The influence of iron metabolism, both on the invading bacterial pathogen and in the host is widespread and often appears to be crucial in determining the outcome of an infection. This study involved the investigation of leukaemia, a clinical disease where abnormal availability of iron may play a part in predisposing patients to bacterial infection. The iron status throughout a Gram-negative septicaemia and in 20 random, newly diagnosed leukaemic patients was assessed. The results revealed that the majority of the patients exhibited high serum iron levels and serum transferrin saturation often at 100%, with an inability to reduce the latter to within normal values during an infection episode. The antibody response to P.aeruginosa, E.coli and K.pneumoniae outer membrane protein (OMP) antigens were investigated by immunoblotting with sequential serum samples during infection in the leukaemic host. Antibodies to all the major OMPs, were observed, although recognition of iron-regulated membrane proteins (IRMPs) was in many cases weak. Results from the enzyme-linked immunosorbent assay indicated that in all patients antibody titre in response to infection was poor. Sub-MICs of mitomycin C significantly altered the surface characteristics of P.aeruginosa. The silver-stained SDS-PAGE gels of proteinase K digested whole cell lysates of strains PAO1, 6750, M7 and PAJ indicated that core LPS was affected in the presence of mitomycin C. In contrast, the rough strain AK1012 showed no observable differences. Results obtained using quantitative gas-liquid chromatographic analysis showed the amount of LPS fatty acids to be unaffected, however, the KDO and carbohydrate content in strains PAO1, 6750 and M7 under Fe+ and Fe- growth conditions were decreased by up to 4-fold in the presence of mitomycin C, indicating perturbed expression of LPS. The cell surface became significantly more hydrophobic in the P.aeruginosa strains, except AK1012 which was comparatively unaffected. The induction of protein G (OprG) in P.aeruginosa was found to be a sensitive indicator of media iron. The data indicated that expression of OprG can be modulated by growth rate/phase, availability of iron and by the presence of ciprofloxacin in the growth medium.

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It has been postulated that immunogenicity results from the overall dissimilarity of pathogenic proteins versus the host proteome. We have sought to use this concept to discriminate between antigens and non-antigens of bacterial origin. Sets of 100 known antigenic and nonantigenic peptide sequences from bacteria were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we were unable to determine a threshold able to separate meaningfully antigen from non-antigen. Thus, antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to the human genome.

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Computational genome analysis enables systematic identification of potential immunogenic proteins within a pathogen. Immunogenicity is a system property that arises through the interaction of host and pathogen as mediated through the medium of a immunogenic protein. The overt dissimilarity of pathogenic proteins when compared to the host proteome is conjectured by some to be the determining principal of immunogenicity. Previously, we explored this idea in the context of Bacterial, Viral, and Fungal antigen. In this paper, we broaden and extend our analysis to include complex antigens of eukaryotic origin, arising from tumours and from parasite pathogens. For both types of antigen, known antigenic and non-antigenic protein sequences were compared to human and mouse proteomes. In contrast to our previous results, both visual inspection and statistical evaluation indicate a much wider range of homologues and a significant level of discrimination; but, as before, we could not determine a viable threshold capable of properly separating non-antigen from antigen. In concert with our previous work, we conclude that global proteome dissimilarity is not a useful metric for immunogenicity for presently available antigens arising from Bacteria, viruses, fungi, parasites, and tumours. While we see some signal for certain antigen types, using dissimilarity is not a useful approach to identifying antigenic molecules within pathogen genomes.

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A nonlinear dynamic model of microbial growth is established based on the theories of the diffusion response of thermodynamics and the chemotactic response of biology. Except for the two traditional variables, i.e. the density of bacteria and the concentration of attractant, the pH value, a crucial influencing factor to the microbial growth, is also considered in this model. The pH effect on the microbial growth is taken as a Gaussian function G0e-(f- fc)2/G1, where G0, G1 and fc are constants, f represents the pH value and fc represents the critical pH value that best fits for microbial growth. To study the effects of the reproduction rate of the bacteria and the pH value on the stability of the system, three parameters a, G0 and G1 are studied in detail, where a denotes the reproduction rate of the bacteria, G0 denotes the impacting intensity of the pH value to microbial growth and G1 denotes the bacterial adaptability to the pH value. When the effect of the pH value of the solution which microorganisms live in is ignored in the governing equations of the model, the microbial system is more stable with larger a. When the effect of the bacterial chemotaxis is ignored, the microbial system is more stable with the larger G1 and more unstable with the larger G0 for f0 > fc. However, the stability of the microbial system is almost unaffected by the variation G0 and G1 and it is always stable for f0 < fc under the assumed conditions in this paper. In the whole system model, it is more unstable with larger G1 and more stable with larger G0 for f0 < fc. The system is more stable with larger G1 and more unstable with larger G0 for f0 > fc. However, the system is more unstable with larger a for f0 < fc and the stability of the system is almost unaffected by a for f0 > fc. The results obtained in this study provide a biophysical insight into the understanding of the growth and stability behavior of microorganisms.

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Immunogenicity arises via many synergistic mechanisms, yet the overall dissimilarity of pathogenic proteins versus the host proteome has been proposed as a key arbiter. We have previously explored this concept in relation to Bacterial antigens; here we extend our analysis to antigens of viral and fungal origin. Sets of known viral and fungal antigenic and non-antigenic protein sequences were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we could not determine a threshold able meaningfully to separate non-antigen from antigen. We conclude that viral and fungal antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to mammalian genomes.

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The 21-day experimental gingivitis model, an established noninvasive model of inflammation in response to increasing bacterial accumulation in humans, is designed to enable the study of both the induction and resolution of inflammation. Here, we have analyzed gingival crevicular fluid, an oral fluid comprising a serum transudate and tissue exudates, by LC-MS/MS using Fourier transform ion cyclotron resonance mass spectrometry and iTRAQ isobaric mass tags, to establish meta-proteomic profiles of inflammation-induced changes in proteins in healthy young volunteers. Across the course of experimentally induced gingivitis, we identified 16 bacterial and 186 human proteins. Although abundances of the bacterial proteins identified did not vary temporally, Fusobacterium outer membrane proteins were detected. Fusobacterium species have previously been associated with periodontal health or disease. The human proteins identified spanned a wide range of compartments (both extracellular and intracellular) and functions, including serum proteins, proteins displaying antibacterial properties, and proteins with functions associated with cellular transcription, DNA binding, the cytoskeleton, cell adhesion, and cilia. PolySNAP3 clustering software was used in a multilayered analytical approach. Clusters of proteins that associated with changes to the clinical parameters included neuronal and synapse associated proteins.

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In Statnote 9, we described a one-way analysis of variance (ANOVA) ‘random effects’ model in which the objective was to estimate the degree of variation of a particular measurement and to compare different sources of variation in space and time. The illustrative scenario involved the role of computer keyboards in a University communal computer laboratory as a possible source of microbial contamination of the hands. The study estimated the aerobic colony count of ten selected keyboards with samples taken from two keys per keyboard determined at 9am and 5pm. This type of design is often referred to as a ‘nested’ or ‘hierarchical’ design and the ANOVA estimated the degree of variation: (1) between keyboards, (2) between keys within a keyboard, and (3) between sample times within a key. An alternative to this design is a 'fixed effects' model in which the objective is not to measure sources of variation per se but to estimate differences between specific groups or treatments, which are regarded as 'fixed' or discrete effects. This statnote describes two scenarios utilizing this type of analysis: (1) measuring the degree of bacterial contamination on 2p coins collected from three types of business property, viz., a butcher’s shop, a sandwich shop, and a newsagent and (2) the effectiveness of drugs in the treatment of a fungal eye infection.

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Fps1p is a glycerol efflux channel from Saccharomyces cerevisiae. In this atypical major intrinsic protein neither of the signature NPA motifs of the family, which are part of the pore, is preserved. To understand the functional consequences of this feature, we analyzed the pseudo-NPA motifs of Fps1p by site-directed mutagenesis and assayed the resultant mutant proteins in vivo. In addition, we took advantage of the fact that the closest bacterial homolog of Fps1p, Escherichia coli GlpF, can be functionally expressed in yeast, thus enabling the analysis in yeast cells of mutations that make this typical major intrinsic protein more similar to Fps1p. We observed that mutations made in Fps1p to "restore" the signature NPA motifs did not substantially affect channel function. In contrast, when GlpF was mutated to resemble Fps1p, all mutants had reduced activity compared with wild type. We rationalized these data by constructing models of one GlpF mutant and of the transmembrane core of Fps1p. Our model predicts that the pore of Fps1p is more flexible than that of GlpF. We discuss the fact that this may accommodate the divergent NPA motifs of Fps1p and that the different pore structures of Fps1p and GlpF may reflect the physiological roles of the two glycerol facilitators.

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We report results of an experimental study, complemented by detailed statistical analysis of the experimental data, on the development of a more effective control method of drug delivery using a pH sensitive acrylic polymer. New copolymers based on acrylic acid and fatty acid are constructed from dodecyl castor oil and a tercopolymer based on methyl methacrylate, acrylic acid and acryl amide were prepared using this new approach. Water swelling characteristics of fatty acid, acrylic acid copolymer and tercopolymer respectively in acid and alkali solutions have been studied by a step-change method. The antibiotic drug cephalosporin and paracetamol have also been incorporated into the polymer blend through dissolution with the release of the antibiotic drug being evaluated in bacterial stain media and buffer solution. Our results show that the rate of release of paracetamol getss affected by the pH factor and also by the nature of polymer blend. Our experimental data have later been statistically analyzed to quantify the precise nature of polymer decay rates on the pH density of the relevant polymer solvents. The time evolution of the polymer decay rates indicate a marked transition from a linear to a strictly non-linear regime depending on the whether the chosen sample is a general copolymer (linear) or a tercopolymer (non-linear). Non-linear data extrapolation techniques have been used to make probabilistic predictions about the variation in weight percentages of retained polymers at all future times, thereby quantifying the degree of efficacy of the new method of drug delivery.

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Representational difference analysis (RDA) has great potential for preferential amplification of unique but uncharacterised DNA sequences present in one source such as a whole genome, but absent from a related genome or other complex population of sequences. While a few examples of its successful exploitation have been published, the method has not been well dissected and robust, detailed published protocols are lacking. Here we examine the method in detail, suggest improvements and provide a protocol that has yielded key unique sequences from a pathogenic bacterial genome. © 2003 Elsevier Science B.V. All rights reserved.