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Discovery of novel bacterial virulence factors and their roles in host-pathogen interactions

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  • Full or part time
    Dr Alan Huett
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Secreted bacterial effector proteins allow many bacterial pathogens to manipulate, subvert and invade host cells to establish and maintain an intracellular niche. Discovery of new effector proteins is challenging since there are no known conserved signal sequences or motifs which are required for effector secretion.
Using a combination of cutting-edge microscopy, cell biology and molecular techniques we will discover and analyse novel bacterial effector proteins and their roles in infection and disease.
This project will involve cloning of bacterial genes, high-throughput transfection of human cell lines, automated image capture and the analysis of multi-colour images to identify novel bacterial effector proteins. Candidate proteins will then be confirmed and their functions elucidated using state-of-the-art molecular and cell biology methods.
These methods and techniques are broadly applicable to many bacterial pathogens and host cell processes, but current interests focus upon pathogenic Escherichia coli and host cell autophagy.

Funding Notes

International Applicants: There are a number of international studentships available,
Normally these studentships provide only tuition fees so applicants should be able to provide at least their own living expenses for the duration of the course.

UK and EU Applicants: Although the vast majority of our home students are fully funded we have traditionally attracted a number of students willing to fund their own training. Home student seeking funded places should see for information about new Research Council funding arrangements.

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

FTE Category A staff submitted: 90.86

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

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