Fitzgerald, Valerie (2015) Tailored bio-molecular screening methodologies for selection of improved antibody lead clones for diagnostic and therapeutic applications. PhD thesis, Dublin City University.
Abstract
The interrogation of highly diverse repertoires of heterogeneous cell populations on a single cell basis increases the likelihood that a cell with unique characteristics will be identified. This thesis describes the development of a new single cell analysis system comprising millions of bundled sub-nanoliter volume bio-incubation chambers for the identification and recovery of target specific antibody secreting cells (ASCs). This Direct Clone Analysis and Selection Technology (DiCAST) is a patented antibody discovery technology that can not only reduce the time and cost for their discovery but has the potential to find candidates that nobody else can. The application of this newly developed technology is applicable to screening both bacterial and mammalian antibody secreting cells and the implementation and feasibility of this platform in identifying target specific antibodies from bacterial and B cell libraries is investigated in this work. It offers a much enhanced alternative to traditional screening approaches in both fields as well as offering drastically improved throughput and multi-plexing capabilities when compared with competing single cell analysis technologies. In addition to development of this enhanced screening approach, complementary methods for automated (ELISA-based) and high throughput (SPR-based) screening of the selected antibodies were developed and deployed for routine use.
Metadata
Item Type: | Thesis (PhD) |
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Date of Award: | November 2015 |
Refereed: | No |
Supervisor(s): | Leonard, Paul and O'Kennedy, Richard |
Subjects: | Biological Sciences > Biotechnology Biological Sciences > Biochemistry Biological Sciences > Immunology |
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 |
Funders: | SFI, EI |
ID Code: | 20760 |
Deposited On: | 17 Nov 2015 14:49 by Ciaran Fagan . Last Modified 01 Sep 2019 03:30 |
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