Use this URL to cite or link to this record in EThOS:
Title: Pathogen detection based on carbohydrate adhesion
Author: Otten, Lucienne
ISNI:       0000 0004 5915 8726
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2015
Availability of Full Text:
Access from EThOS:
Access from Institution:
The rapid detection of pathogenic organisms to ensure appropriate administration of treatment remains a global healthcare challenge. This is becoming increasingly difficult, as identification of the organism alone is no longer enough, with the rise of drug resistance amongst many pathogens it is becoming increasingly important that both the pathogen and drug resistance are identified. Currently, rapid identification can be achieved through a variety of techniques. However, many of these techniques are expensive, require extensive sample preparation, or highly trained personnel to run with results often not rapidly available. This leaves health care professionals to make point-of-care treatment decisions based on symptoms without any indication of drug resistance. The use of carbohydrate microarrays for pathogen detection has been identified as both a method for detection but also as a basis for identifying new drug targets. This exploits the initial protein-carbohydrate interaction that many pathogens utilise in the initial stages of infection. However, the use of microarrays is also challenging, as highly sensitive identification of pathogens often requires expensive or synthetically challenging oligosaccharides or coupling with a highly sensitive detection method thus limiting its point of care application. Herein we describe the coupling of a facile surface chemistry for glycan addition with a powerful statistical algorithm to improve the sensitivity of a cheap monosaccharide functionalised surface without using expensive detection methodologies. This technique was then applied to the detection and identification of toxic lectins, bacterial samples and finally the life-stage specific detection of Plasmodium falciparum (one of the parasites responsible for human malaria). In this last case, drug resistance related to carbohydrate binding profile was also observed.
Supervisor: Not available Sponsor: Biotechnology and Biological Sciences Research Council ; Systems Biology Doctoral Training Centre
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QP Physiology