Predicting Effective Targets for Novel Antimicrobials: Probing an Essential Signalling Network in Burkholderia Pseudomallei as a Test Case - Biosciences, PhD (BBSRC SWBio DTP Funded)

The South West Biosciences Doctoral Training Partnership (SWBio DTP) is a BBSRC-funded PhD training programme in the biosciences, delivered by a consortium comprising the Universities of Bristol (lead), Bath, Cardiff, Exeter, and Rothamsted Research. Together, these institutions present a distinctive cadre of bioscience research staff and students with established international, national and regional networks and widely recognised research excellence. The partnership has a strong track record in advancing knowledge through high quality research and teaching in partnership with industry and government.

This project is one of a number that are in competition for funding from the South West Biosciences Doctoral Training Partnership (SWBio DTP). Up to 4 fully-funded studentships are being offered to start in September 2018 at the University of Exeter.

Supervisory team:

Main supervisor: Dr Steven Porter
Co-supervisor: Prof Ravi Acharya
Collaborator: Prof Rick Titball

Location:

University of Exeter, Streatham Campus, Exeter

Project Description:

Bacterial survival depends upon their ability to respond to potential threats such as environmental stresses, attack by the host’s immune system and antibiotics. Threats are detected using sensors (kinases), which trigger responses and ensure survival. Some bacteria have hundreds of sensors and while most of these sensors work independently (Figure 1A), the more important decisions affecting processes such as survival, virulence and antibiotic resistance, can rarely be made based on a single signal. Instead multiple different signals must be assessed and this requires the use of a network where multiple sensors work together to detect multiple different signals and to make the correct decision (a multikinase-network; Figure 1B). In the era of ever- increasing antibiotic resistance, these networks make attractive potential drug targets as they are absent from humans and are needed for bacterial survival and virulence. However, a major roadblock in researching these networks is determining which sensors participate in them. We have developed a bioinformatic method that allows us to predict these sophisticated networks and will therefore streamline the process of discovering these promising drug targets.

This project is focussed on a unique multikinase-network that we have predicted in the melioidosis pathogen, Burkholderia pseudomallei, which comprises two sensor kinases that are essential for cell growth. It is likely to be an excellent target for the development of 4 / 16 antimicrobial drugs.

Research Objectives:

1. Show that the sensors work together as a network using interaction assays (twohybrid and phosphorylation assays).

2. Determine what this network controls and why it is essential.

3. Identify the stimuli sensed by the kinases using binding assays and structural characterisation of the sensory domains using X-ray crystallography.

Achieving these objectives will, firstly, characterise a crucial multikinase-network in an important antibiotic resistant pathogen and secondly, by validating our method for predicting multikinasenetworks will greatly accelerate the discovery of other examples of these promising potential drug targets.

Rotations:

1. Steve Porter and Rick Titball: Predicting multikinase-networks in Burkholderia pseudomallei. Skills gained: bioinformatic analysis of specificity residues, molecular biology and protein-protein interaction assays.

2. Ravi Acharya: Structural biology of the essential kinases in Burkholderia pseudomallei. Skills gained: protein purification and X-ray crystallography.

Training potential:

The student will develop a broad range of interdisciplinary skills important for systems biology research including: molecular microbiology, protein biochemistry, structural biology, bioinformatics, sequence analysis and molecular biology.

Entry requirements:

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. Applicants with a Lower Second Class degree will be considered if they also have Masters degree or have significant relevant non-academic experience.

In addition, due to the strong mathematical component of the taught course in the first year and the quantitative emphasis in our projects, a minimum of a grade B in A-level Maths or an equivalent qualification or experience is required.

If English is not your first language you will need to have achieved at least 6.5 in IELTS and no less than 6.5 in any section by the start of the project. Alternative tests may be acceptable, please see http://www.bristol.ac.uk/study/language-requirements/profile-c/.

Students from EU countries who do not meet the residency requirements may still be eligible for a fees-only award but no stipend. Applicants who are classed as International for tuition fee purposes are not eligible for funding. Further information about eligibility can be found in the following document: http://www.bbsrc.ac.uk/documents/studentship-eligibility-pdf/