Investigating roles of RNA editing in virus host interaction

Su, Shuquan

Investigating roles of RNA editing in virus host interaction

Su, Shuquan

Permalink

Publication Type:: Thesis
Issue Date:: 2024

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download thesisAdobe PDF (22.12 MB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Su, Shuquan
dc.date.accessioned	2025-07-01T03:20:04Z
dc.date.available	2025-07-01T03:20:04Z
dc.date.issued	2024
dc.identifier.uri	http://hdl.handle.net/10453/188018
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	The losses incurred during the COVID-19 pandemic underscore the urgent need to study host adaptations of emerging pathogens and their life cycles. The virus infection cycle comprises several key steps, including virus entry and gene expression, both crucial for understanding host adaptation. This thesis focuses on these processes, particularly the role of RNA editing in viral infections. RNA editing, catalysed by ADAR and ADAT enzymes, modifies viral mRNA and host tRNA, influencing multiple aspects of viral gene expression. Statistical analysis of codon usage biases between human and non-human viruses revealed usage differences associated with ADAR and ADAT editing. Machine learning models, using mainly Relative Synonymous Codon Usage (RSCU) features, successfully predicted virus-host relationships, generating a virus codon fitness (VCF) score to assess codon fitness in hosts. These findings demonstrate the potential of machine learning in predicting host adaptation of emerging viruses. Virus entry depends on protein-protein interactions (PPI) between viral Spike proteins and host receptors. A newly developed FRET-based assay detected interactions between SARS-CoV-2 Spike and human ACE2/TMPRSS2. Additionally, RNA sequencing identified RNA editing events in these receptors, suggesting potential regulatory mechanisms in virus entry. These insights enhance our understanding of viral adaptation and offer predictive tools for emerging pathogens.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/188018/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2024 Shuquan Su
dc.rights	au.edu.uts.lib/cph
dc.title	Investigating roles of RNA editing in virus host interaction	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

The losses incurred during the COVID-19 pandemic underscore the urgent need to study host adaptations of emerging pathogens and their life cycles. The virus infection cycle comprises several key steps, including virus entry and gene expression, both crucial for understanding host adaptation. This thesis focuses on these processes, particularly the role of RNA editing in viral infections. RNA editing, catalysed by ADAR and ADAT enzymes, modifies viral mRNA and host tRNA, influencing multiple aspects of viral gene expression. Statistical analysis of codon usage biases between human and non-human viruses revealed usage differences associated with ADAR and ADAT editing. Machine learning models, using mainly Relative Synonymous Codon Usage (RSCU) features, successfully predicted virus-host relationships, generating a virus codon fitness (VCF) score to assess codon fitness in hosts. These findings demonstrate the potential of machine learning in predicting host adaptation of emerging viruses. Virus entry depends on protein-protein interactions (PPI) between viral Spike proteins and host receptors. A newly developed FRET-based assay detected interactions between SARS-CoV-2 Spike and human ACE2/TMPRSS2. Additionally, RNA sequencing identified RNA editing events in these receptors, suggesting potential regulatory mechanisms in virus entry. These insights enhance our understanding of viral adaptation and offer predictive tools for emerging pathogens.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/188018