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Title: Combined systems approaches to understand host-pathogen interactions
Author: Kozlowska, Justyna
ISNI:       0000 0004 5355 1631
Awarding Body: King's College London (University of London)
Current Institution: King's College London (University of London)
Date of Award: 2015
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Systems biology studies are becoming increasingly important as the need to study organisms in a holistic manner, instead of looking at processes in isolation, is being recognised. This is especially true for the study of host-pathogen interactions where the responses from bacteria are complex and overlap extensively. This thesis explores the application of 1H NMR metabolomics to the study of bacteria host interactions and seeks to identify its strengths and weaknesses with a view to integrating this technique into a combined approach that can provide an unprecedented, sophisticated understanding of host-pathogen interactions that we believe is intractable by other methodologies. The BBSRC CASE studentship that supported this work was awarded in conjunction with Procarta Biosystems Ltd who have produced a new generation of antibiotics with a novel mechanism of action. The final objective for the studentship therefore, was to develop a validated systems approach capable of defining the mechanism of action of this new class of antibiotics; transcription factor decoys (TFDs). By understanding how the target bacteria respond to antibiotic threats, the future development of new targets, delivery systems and formulations can be undertaken in a rational manner. The thesis builds towards this ultimate goal in three stages by showing, in a stepwise manner, how three increasingly complex scenarios can be interrogated by NMR metabolomics, either as a standalone technique or in combination with biophysical or genomic tools. In the first stage we investigated how the growth of different Pseudomonas aeruginosa isolates from Cystic Fibrosis patients might influence airway secretions. Growth and NMR analysis of the spent media was technically challenging, highlighting the need for improved data pre-processing techniques and experimental design. Nevertheless multivariate analysis of changes in spent media composition could be related to univariate clinical measures of respiratory disease. In the second stage we undertook a murine faecal microbiome study to show how different gut microbial communities affect the host gut metabolome. Faecal pellets were extracted into aqueous buffer and 1H NMR spectra obtained in the solution state. Clear differences in the amino acid and short chain fatty acid complement of the mouse gut were related to divergence in the gastrointestinal microbiota in the mice. The study required comparison of two separate sets of multivariate data and showed how, with application of Hierarchical Cluster Analysis, relationships between microbiota can be simplified to generate hypotheses that can be tested using metabolomic approaches. In this study the metabolomic technique was capable of identifying a link between divergence of gut microbiota and the nutritional performance of the mouse gut. In the third and final stage, we investigated whether a whole organism view could provide a bacterial perspective to enable a better understanding of how bacteria respond to antibiotic challenges. Here we combined 1H NMR spectroscopy, now of solid, bacterial cell samples (using high resolution magic angle spinning), with electron microscopy and transcriptomics to characterise the effect on Escherichia coli of four structurally and physically related antimicrobial peptides with suspected differences in their mechanisms of action. Bacterial responses characterised by the NMR metabolomic study could be detected at sub-lethal antimicrobial peptide concentrations and were qualitatively dierent according to the antimicrobial peptide. The technique was sufficiently sensitive and highthroughput to allow both a range of antimicrobial peptide concentrations to be probed as well as the bacterial response to be followed over time. Using the NMR technique to identify optimal conditions for GeneChip experiments allowed the antimicrobial peptide mechanism of action to be inferred from analysis of the ontological profile of those genes whose expression is altered in response to the antibiotic challenge. This study provided a fresh, novel perspective for previous functional and biophysical studies and shows that, with better integration with transcriptomic and other systems data, 1H NMR metabolomics will have considerable value in the study of host-pathogen interactions.
Supervisor: Mason, Andrew James ; Bruce, Kenneth Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available