With a population both increasing in number and age, comes a need for new diagnostic tools in the healthcare system, capable of diagnosing and monitoring multiple disorders in a cheap and effective way to provide personalised healthcare. Multiplex label-free biosensors have the potential to rejuvenate the current system. This thesis details the assessment of an ‘in house’ built labelfree array screening technology that has potential to be a point-of-care diagnostic for personalised medicine – the Array Reader. The performance of the Array Reader platform is considered in detail and optimised for both antibody and protein screening arrays. A Global Fit protocol is developed to extract kinetic constants for all protein-protein interactions, assuming a Langmuir adsorption binding model. Standard operating procedures are developed to provide optimised dynamic range, sensitivity, reproducibility and limit of detection of immuno-kinetic assay. A new antibody bio-stack signal amplification strategy is formed, improving the detection limit 60-fold. As a consequence, the bio-stack resulted in a novel method for determining the plasmon field penetration depth, defining the assay sensing volume at the nanoparticle surface. Antibody screening arrays were investigated with an IgG quantification assay to determine total IgG content from serum samples. It relied on the ability of protein A/G to bind antibodies via the Fc region. Specific antigens were used to measure the binding properties of the antibody Fab region. By characterising both regions, we have gained insight into the overall ability of an antibody to trigger an immune response. Protein screening assay were investigated targeting C-reactive protein (CRP), a marker of inflammation. The assays performance characteristics compared favourably with clinically used CRP assays. Finally, an antibody screening array was developed to assess the efficacy of a vaccine against Yersinia pestis in a non-human primate model. The vaccine screening array is an excellent example of the versatility of the platform and just one of many possible applications for the future.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:601390 |
Date | January 2013 |
Creators | Read, Thomas |
Contributors | Shaw, Andrew |
Publisher | University of Exeter |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://hdl.handle.net/10871/14742 |
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