Brennan, Joanne (2005) The production of recombinant single chain antibody fragments for the detection of illicit drug residues. PhD thesis, Dublin City University.
Abstract
Recombinant antibodies represent a more sensitive and specific detection tool for immunoanalysis. The research carried out for this thesis describes the production of genetically-derived single chain antibody fragments to detect illicit drugs.
A variety of novel recombinant antibody fragments against morphine-3-glucuronide, a metabolite of heroin has been produced. A monomeric, dimeric and enzyme-labelled scFv were characterised with respect to their binding abilities and cross reactivities. Monomeric scFv was successfully applied to a competitive ELISA format for the detection of morphine residues in saliva. The assay was used to positively identify morphine residues in the saliva of drug addicts attending a rehabilitation clinic. An inhibition assay to detect morphine in saliva was also developed using the BIAcore 3000 instrument, a surface plasmon resonance-based biosensor for detection of biomolecular interactions in ‘real-time’. A novel sol particle lateral flow immunoassay was generated using monomeric and dimeric scFvs for the detection of M3G.
Recombinant antibody fragments against tetrahydrocannabinol were isolated from a naive human library by a process known as biopanning. Phage-displayed antibodies have been fully characterised with respect to their binding capabilities and were successfully applied to an immunoassay for the detection of marijuana residues in saliva.
Metadata
Item Type: | Thesis (PhD) |
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Date of Award: | 2005 |
Refereed: | No |
Supervisor(s): | O'Kennedy, Richard |
Uncontrolled Keywords: | illicit drug detection; heroin; recombinant antibodies; genetically-derived single chain antibody fragments |
Subjects: | Biological Sciences > Biotechnology Biological Sciences > Biosensors |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Science and Health > School of Biotechnology |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License |
ID Code: | 17319 |
Deposited On: | 29 Aug 2012 10:28 by Fran Callaghan . Last Modified 19 Jul 2018 14:56 |
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