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Title: Computational approaches to the analysis of the T cell receptor repertoire
Author: Best, K.
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2016
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The T cell receptor (TCR) repertoire has the potential to be a highly personalised biomarker of historic or current immune challenges, and may hold clinically relevant information. This thesis reviews aspects of the measurement and analysis of the TCR repertoire, including approaches to obtaining high-throughput sequencing data and using these data to investigate features of the repertoire in health and disease. The thesis then considers three topics related to computational and experimental analysis of the TCR repertoire. First, this thesis explores a technical challenge in obtaining accurate quantitative TCR repertoire sequence data, observing substantial heterogeneity in the PCR amplification step essential for most current high-throughput sequencing protocols. An important conclusion of this chapter is that single molecule barcoding before amplification is essential to obtain robust quantification of clone abundances from sequence data. The second chapter considers the challenges of producing an effective TCR repertoire which can provide broad coverage of potential pathogens while maintaining tolerance to self-peptides. A computational model is explored which incorporates a linear programming representation of peripheral tolerance, with dendritic cells acting as the central agents reshaping the T cell population. The model is shown to maintain a population with restricted responsiveness to self-peptides while retaining a diverse and cross-reactive repertoire. In the final results chapter, TCR repertoire data from immunised mice is used to demonstrate that within a simplified animal model of immune response, the antigen responsive CDR3βs are almost completely private. However, exploration of the protein sequences of the antigen associated CDR3βs suggests that there may be amino acid motifs defining the antigen response. Overall, this thesis demonstrates the application of computational and modelling approaches to address questions regarding the TCR repertoire, facilitating interpretation of high-throughput sequencing data and providing insight into maintenance of diversity in the peripheral T cell population.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available