Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.735881
Title: Whole genome sequencing (WGS) as a unified platform for outbreak identification and resistance prediction in Staphylococcus aureus
Author: Gordon, Nicola
ISNI:       0000 0004 6500 618X
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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Abstract:
Staphylococcus aureus continues to present challenges to modern healthcare, due to its acquisition of antimicrobial resistance factors, its ability to cause invasive infections associated with significant morbidity and mortality, and its propensity for person-to-person transmission resulting in outbreaks. For outbreak investigation, current typing methods lack resolution, and the relatively slow turnaround times may hinder effective infection control intervention. Whole-genome sequencing (WGS) is rapidly becoming faster and more affordable, offering increased resolution in a comparable timeframe. Having the entire genome means the data can also be explored for resistance and virulence testing. In this thesis, I explore the use of WGS for investigating outbreaks and for predicting antimicrobial resistance phenotype. First, I establish the genetic diversity in the nasal S. aureus population at acquisition and after long-term carriage, to determine the effect of within-host diversity on outbreak WGS interpretation. I then use 15 well characterised S. aureus outbreaks to develop an WGS approach for outbreak investigation. I test this approach by applying WGS to a further 5 outbreaks where the infection control investigation was inconclusive. Combining the epidemiological and WGS data from all 20 outbreaks, I then evaluate whether the WGS data can be used to predict the possibility of a long-term carrier involved in maintaining an outbreak, and apply this in real-time using a rapid turnaround benchtop sequencer. Finally, I explore the use of WGS for predicting antimicrobial resistance phenotype. I conclude that, for outbreaks, WGS has enhanced resolution compared to standard techniques and can give additional information to aid the outbreak investigation. For antimicrobial resistance, WGS is as sensitive and specific as routine testing methods. WGS provides a promising alternative to traditional culture and typing methods for enhancing our understanding of S. aureus and ultimately other pathogens.
Supervisor: Kearns, Angela ; Peto, Tim ; Walker, Sarah Sponsor: Medical Research Council ; Department of Health ; Wellcome Trust
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.735881  DOI: Not available
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