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Title: Metagenomic next generation sequencing for viral pathogens : application and validation of a deployable sequencer for virus identification
Author: Kafetzopoulou, Liana
ISNI:       0000 0004 9358 6708
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2020
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Viral pathogen identification and discovery is of significant importance to clinical virology and public health. Rapid and unbiased diagnostic methods are vital when developing a strategy for treatment and eradication of an emerging pathogen. Advances in the field of sequencing over the last decade have facilitated pathogen identification without prior knowledge, introducing its potential and importance as a diagnostic support approach. More recently the development of the MinION, a portable palm-sized sequencing device run via a laptop computer has introduced sequencing in real time in remote settings and overcome many limitations of its predecessors. The objective of this project was to investigate the possibility of nontargeted viral pathogen identification and full genome recovery from clinical samples utilising a metagenomic sequencing approach coupled with the MinION. The limitations and bottlenecks identified during initial experiments using a model system of Hazara virus spiked into human serum and preliminary clinical sample testing allowed for the development and optimisation of a pipeline for clinical sample processing. It was subsequently demonstrated that direct metagenomic sequencing of clinical serum samples in a laboratory setting can elucidate full viral genomes directly from clinical samples for Chikungunya, Dengue and Lassa virus across a range of clinically relevant viral titres. Finally, to evaluate metagenomic nanopore sequencing for the recovery of whole viral genome sequences from clinical samples of a divergent virus in a remote and resource-limited setting, metagenomic nanopore sequencing of Lassa virus was implemented in Nigeria during the 2018 endemic season, providing vital public health information in real-time.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral