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Antibody-like proteins (Affimers) against Influenza virus: development of tools to diagnose and treat the flu

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  • Full or part time
    Dr Juan Fontana
    Dr D Tomlinson
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Influenza virus is a current public health risk. 5-10% of adults are yearly affected by seasonal Influenza outbreaks, leading to up to 5 million cases of severe illness and 500,000 deaths worldwide. Additionally, Influenza can develop resistance to current antivirals and new strains can emerge, resulting in pandemics.

Currently, the most effective way to prevent disease is vaccination. This results in the production of antibodies that protect individuals against the specific strains included in the vaccine composition. Therefore, this approach greatly relies on anticipating which strains will be the most abundant ones on a particular year. However, this system is not fool proof. For example, it was recommended by the World Health Organisation that vaccines for use in 2017-2018 should contain the Influenza B/Brisbane strain (plus two other Influenza A strains) (1); however, during this winter season the Influenza B/Yamagata strain has been predominant in the UK, resulting in an increased number of Influenza infections (2).

The discovery that broadly neutralising antibodies are sometimes produced by infected people, suggested that if they could be produced by an individual after the administration of a vaccine, there would be no need for yearly vaccinations (3). However, this approach has been proven difficult to implement.

We have developed an artificial binding protein, termed Affimer (4), based on a constant scaffold protein that contains two randomised loop regions for molecular recognition. This scaffold protein is extremely stable at high temperatures, and is expressed well in bacteria, allowing for large production at low costs.

Based on this exciting platform, we propose a work plan to explore the production of anti-Influenza Affimers with the aim of generating the following tools:

1.- A diagnostic tool for Influenza infection. The development of Affimers that can recognise an Influenza infection would allow to produce a rapid diagnostic test to identify if a patient has been infected by Influenza. This would allow avoiding using antibiotics (which are only effective against bacteria and wide-spread use is contributing to the epidemic of antibiotic microbial resistance), and the use of Influenza-specific antivirals.

2.- An Affimer cocktail for prophylactic and therapeutic use. Most Influenza antibodies work by blocking the function of the viral fusion protein haemagglutinin, and therefore preventing viral entry inside the host cell (5). The development of Affimers with an effect on a broad range of Influenza strains that mimic the function of these antibodies, would allow treatment of people at high risk of developing Influenza-related complications and/or in the event of a pandemic, similarly to current antibody treatments against Ebola and other viruses (6). This approach will not only allow us to target universal Influenza epitopes that antibodies struggle to target, but also would open the possibility to develop drugs that mimic the structure of the produced Affimers.

Supervisors are experts in Influenza virus entry, structural biology and protein engineering. Techniques to be employed include Affimer production, Influenza activity assays and structural approaches (cryo-electron microscopy and X-ray crystallography).

The successful applicant will join the Faculty of Biological Sciences Post-Graduate Research Program at the University of Leeds with over 100 talented and motivated post graduate students passionate about research. Understanding the molecular basis of replication and pathogenesis of important human and animal viruses and structural biology are two of the main strengths of FBS at UoL (http://www.fbs.leeds.ac.uk/research/).

Applicants should hold or expect a first/upper second-class degree or equivalent in a relevant subject and/or a Masters degree in a relevant subject. Knowledge of at least one of the following techniques is required (practical experience would be an advantage): virology and cell culture; protein expression and purification; structural biology approaches.

Funding Notes

Project is eligible for funding under the FBS Faculty Studentships scheme. Successful candidates will receive a PhD studentship for 4 years, covering fees at UK/EU level and stipend at research council level (£14,777 for 2018-19).
Candidates should have, or be expecting, a 2.1 or above at undergraduate level in a relevant field. If English is not your first language, you will also be required to meet our language entry requirements. The PhD is to start in Oct 2018.
Please apply online here https://studentservices.leeds.ac.uk/pls/banprod/bwskalog_uol.P_DispLoginNon Include project title and supervisor name, and upload a CV and transcripts.


1.- World Health Organization: Recommended composition of influenza virus vaccines for use in the 2017-2018 northern hemisphere influenza season. http://www.who.int/influenza/vaccines/virus/recommendations/201703_recommendation.pdf?ua=1
2.- Public Health England: Letter to All GPs, January 2018: https://www.england.nhs.uk/south/wp-content/uploads/sites/6/2018/01/high-level-flu-gp-letter-jan-18.pdf
3.- Krammer. Novel universal influenza virus vaccine approaches. Curr Opin Virol. 2016; 17:95-103.
4.- Tiede et al. Affimer proteins are versatile and renewable affinity reagents. Elife. 2017;6 pii: e24903.
5.- Fontana and Steven. Influenza virus-mediated membrane fusion: Structural insights from electron microscopy. Arch Biochem Biophys. 2015; 581:86-97.
6.- Both et al. Monoclonal antibodies for prophylactic and therapeutic use against viral infections. Vaccine. 2013; 31(12):1553-9.

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

FTE Category A staff submitted: 60.90

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

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