Holt, Giles (2018) Characterising the impact on bacterial physiology of phage infection and phage as a tool to support microbiota studies. Doctoral thesis, Northumbria University.
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Text (Doctoral thesis)
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Abstract
Shiga-toxigenic encoding Escherichia coli are a global health concern. Carriage of the shigatoxin gene increases the pathogenicity of the bacteria as the toxin has downstream impact on clinical disease. Enterohaemorrhagic E. coli (EHEC) symptoms lead from mild to severe bloody diarrhoea, where the toxin targets protein synthesis in specific cells preceding cell death and clinical sequalae including; haemolytic ureamic syndrome (HUS), haemorrhagic colitis (HC) and thrombotic thrombocytopenic purpura (TTP). This toxin is carried by temperate lambdoid-like bacteriophages. How temperate bacteriophages play a role in microbial infection and disease progression is poorly understood but less is known of the extent in which they impact on microbial communities. Their role in bacterial adaptation and evolution is essential as they carry genes that promote positive evolutionary selection for the lysogen.
This study focuses on 4 key areas. The first compares previously studied Biolog phenotype microarrays to comparative metabolite profiling to study the impact of Shiga toxin-prophage ɸ24B on its Escherichia coli host MC1061. As a lysogen, this study determines that the prophage alters the bacterial physiology by increasing the rates of respiration and cell proliferation. This is the first reported study detailing phage-mediated control of the E. coli biotin and fatty acid synthesis that is rate limiting to cell growth. Through ɸ24B conversion the lysogen also gains increased antimicrobial tolerance to chloroxylenol and 8-hydroxyquinoline and other antimicrobials. When comparing the metabolic profiles between MC1061 and the ɸ24B lysogen in standard culture, and when treated with 2 antimicrobials, discreet differences are observed. This is also the first reported use of metabolite profiling to characterise the physiological impact of lysogeny under antimicrobial pressure. The study demonstrates that ɸ24B does not need to carry any distinguishable antimicrobial resistance genes to confer tolerance to antimicrobials.
The second focus further studies ɸ24B conversion of E. coli MC1061. It demonstrates that during growth increased resistance by the lysogen is acquired over time when challenged with increasing concentrations of 8-hydroxyquinoline and chloroxylenol. Using targeted GC-MS of the cell wall fatty acid structure the study shows that under optimal conditions the prophage alters the physiology of its host cell by decreasing the total fatty acid composition. Due to the biotin pathway being intrinsically linked to the fatty acid synthesis pathway, it is probable that a similar mechanism is employed by ɸ24B. Intriguingly distinct strategies in host cell wall fatty acids are noticed when treated with antimicrobials 8-hydroxyquinoline or chloroxylenol. When under challenge with either antimicrobial there is an increase in the total cell wall fatty acids in the lysogen, with significant increases observed in the presence of 8-hydroxyquinoline. From this study it can be hypothesised that when the host is not challenged by the antimicrobial, the phage manipulates the fatty acid synthesis pathway to redirect energy and resources from cell wall physiology. Further hypothesis can be made that under initial antimicrobial challenge, phage infection promotes broad antimicrobial tolerance by increasing total cell wall lipids, significantly increasing fatty acids that alter membrane fluidity. The observed tolerance increases exponentially over 24 hours compared to the naïve host, where the phage acquires true resistance by directing an alternative resistance mechanism to that of the cell wall fatty acid composition.
The third area focuses on design of a metabolomic program (CCRACD) that was completed to aid analysis downstream of discovery analysis software. Analysis of metabolite features over several conditions and file outputs is often difficult especially if chromatographic alignment offers error. Often steps in analysis between compound identification and plotting require laborious manual data mining to create profiles for compounds of interest that extend over several conditions. Metabolic profiling was achieved through construction of several bourne/bourne again (sh/bash) scripts and plots of the tabulated data were carried out using R scripts. The scripts were wrapped in a gui to make a user-friendly tool.
The fourth chapter illustrates the design of a genomic program (GGOSS) built to aid study in chapter 7. Genomic analysis using open source software (OSS) in a linux operating system has become standard practice for many genomic studies. However the increasing need to run analysis on a larger scale, to demonstrate the use of multiple tools for each step, and the amount of steps still required to be done by hand/eye, has been a challenge for researchers without a programming background. Over the years many programs have been built to broach this, which have high cost and/or strict pathways/tools and/or are web based (server/connection dependent). Recent initiatives like the MRC funded CLIMB have been developed to overcome this, but again this is driven at the command line. This research informed construction and development of a bioinformatics tool that provides a free, installable GUI, with simple OSS installation, intuitive use, simple drag and drop for mass files, saveable tool setting menus and pipelines, and comparative OSS tools. GGOSS enables scientists to run genomic analysis without the need for prior computing skills, but with a working knowledge of the analysis to complete.
Finally, this study investigates the developing gut microbiota of very preterm infants. Necrotising enterocolitis (NEC) and late onset infection remain major causes of morbidity and mortality in those born preterm. The bacterial microbiota of preterm neonates has been widely studied: dysbiosis appears key to disease development, yet how this occurs is poorly understood. This study compares gut bacteria and bacteriophages over an 8 week period in 2 twin pair sets, plus one individual child. All children are extremely premature and were residing on the neonatal intensive care unit (NICU), Royal Victoria Infirmary, Newcastle upon Tyne. Massively parallel DNA sequencing was used to profile the bacterial, fungal, free virus and chemically induced lysogenic viruses from preterm infant stool to overlay analyses. Community structure and viral metagenomics were compared against clinical data to assess the impact of combining all techniques. Greater resolution in microbiotal dissimilarity between individual infants and twin pairs was observed with the inclusion of lysogenic bacteriophages, and even more so with free virus data. Lysogenic communities showed strongest similarities to the bacterial communities, reflecting bacterial viability. Bacterial taxonomic richness increased over time in all patients. Decrease in viral richness was seen in infants who remained healthy. This study demonstrates the potential importance of complementary viral community analysis in evaluating the role of microbiota stability and dysbiosis in disease states.
Item Type: | Thesis (Doctoral) |
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Uncontrolled Keywords: | Phage increase bacteria antimicrobial resistance, Phage metabolomics, Phage alter bacterial cell wall, Viral community analysis as sensitive biomarker of disease, Genome sequencing bioinformatic tools |
Subjects: | C500 Microbiology |
Department: | Faculties > Health and Life Sciences > Applied Sciences University Services > Graduate School > Doctor of Philosophy |
Depositing User: | Paul Burns |
Date Deposited: | 21 Jun 2019 14:00 |
Last Modified: | 31 Jul 2021 22:32 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/39781 |
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