Investigation and comparison of the human interactions of flaviviral NS5 protein

  • Jack Hales

Student thesis: Master's ThesisMaster of Science by Research (MScR)


Dengue virus and Zika virus are both emerging flaviviruses and pose growing risks to the global human population. Despite numerous links being drawn on the similarities of both viruses, there have been no direct, large-scale comparisons of the interactomes of these two viruses. With NS5 playing such an important central role with virus-host interactions, the similarities between this protein’s interactors could advance our understanding of the evolutionary closeness between the species and inform future studies about the potential for dengue-developed therapeutic host targets to be utilised for Zika fever. It would also provide a side-by-side comparison to show the differences in interactome that may explain the biological differences between dengue and Zika virus. Using transfected HEK-293-Flp cells as a viral gene expression system and pulldown LCMS/MS proteomics, the similarities and differences between ZNS5 and DENV-NS5 interactors are explored, revealing that differences lie largely at the individual protein level with mostly similar pathways being targeted by both viruses. The comparability of different proteomic programmes and pulldown techniques was also investigated with a comparison between MaxQuant and Proteome Discoverer revealing large differences in the data generated from the sample spectra at both the protein identification level and in large scale pathways analysis with STRING and DAVID. BioID-labelling and FLAG-tag pulldowns were also compared with the intention to investigate the differences in interactomes generated by these two methods which once again highlighted the potential for differences in LC-MS/MS proteomics to arise. Cdk1 and UBR5, two ZNS5-specific interactors detected robustly by LC-MS/MS proteomics, were then validated as interactors in reverse-pulldowns and western blots to test the reliability of LC-MS/MS proteomics but called into question the quantitative aspects of the technique by also pulling down DENV-NS5 which further highlighted current limitations in predictive proteomics.
Date of Award23 Jan 2019
Original languageEnglish
Awarding Institution
  • The University of Bristol
SupervisorAndrew D Davidson (Supervisor)

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