Don't miss our weekly PhD newsletter | Sign up now Don't miss our weekly PhD newsletter | Sign up now

  Predicting the next pandemic: drivers of the emergence of RNA viruses


   School of Biological Sciences

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Prof M Woolhouse, Prof Amy Pedersen  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

**PLEASE NOTE – the deadline for requesting a funding pack from Darwin Trust has now passed and completed funding applications must be submitted to Darwin Trust by 19th January. We can still accept applications for this project from self-funding students.

This project is about identifying candidates for Disease X, the next pandemic pathogen. The Woolhouse and Pedersen labs are taking an ecological and evolutionary approach to research on this hugely topical problem.

We have assembled a substantial database on the characteristics of the entire set (more than 200) of human RNA viruses. New ones are being discovered at the rate of 2-3 per year. Genome sequence data have been published for most of these viruses and the number of sequences available from natural infections of non-human mammals/birds is increasing exponentially. This affords unprecedented opportunities to investigate the evolutionary origins of human viruses through genomic analysis. Using discrete traits analysis, sequence data will be integrated with existing information on virus phenotypes, including known host range, transmission route and other variables.

A key determinant of virus biology is cell receptor usage. Cell receptor determines host range, tissue tropism, pathogenicity and transmissibility. The evolution of cell receptor usage is not well understood but the growth of proteomics databases that infer protein-protein interactions have opened up new avenues for research on this topic.

Data modelling will involve a combination of phylogenetic and evolutionary models, computational biology and machine learning methods. The student will receive one-to-one training in the use of state-of-the-art software platforms for implementing these powerful techniques. Broader training will be provided, as required, in bioinformatics, data science and epidemiology, plus access to considerable expertise in molecular virology.

Our earlier work in this field has contributed to both WHO and CDC policy on emerging viruses. This project will help to establish whether the search for new viruses with pandemic potential should focus on a narrow subset of virus taxa or whether a less targeted approach is preferable. An anticipated output of this new project is recommendations for strategies for surveillance for potential zoonotic viruses, a hotly debated topic.

Good computational and statistical skills are required, as well as an interest in applying these skills to biological problems of global public health significance. The successful applicant will not necessarily be familiar with the analytical approaches needed, but should be able to demonstrate an aptitude and enthusiasm for learning and applying new skills. A background in biology, genetics, or epidemiology/ public health with good quantitative skills would be ideal.

For further information on the Woolhouse and Pedersen labs please see our websites: www.epigroup.biology.ed.ac.uk and https://pedersen.bio.ed.ac.uk.

The School of Biological Sciences is committed to Equality & Diversity: https://www.ed.ac.uk/biology/equality-and-diversity

Biological Sciences (4) Mathematics (25)

Funding Notes

The “Institution Website” button on this page will take you to our Online Application checklist. Please carefully complete each step and download the checklist which will provide a list of funding options and guide you through the application process. From here you can formally apply online. Application for admission to the University of Edinburgh must be submitted by 5th January 2022.

References

Woolhouse, M.E.J. and Brierley, L. (2018). Epidemiological characteristics of human-infective RNA viruses. Scientific Data 5: 180017.
Brierley, L., Pedersen, A.B. and Woolhouse, M.E.J. (2019). Tissue tropism and transmission ecology predict virulence of human RNA viruses. PLoS Biology 17: e3000206
Zhang, F., Chase-Topping, M., Guo, C.-G., van Bunnik, B.A.D., Brierley, L. and Woolhouse, M.E.J. (2020). Global discovery of human-infective RNA viruses: a modelling study. PLoS Pathogens 16: e1009079

How good is research at University of Edinburgh in Biological Sciences?


Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

Where will I study?

Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.