BBSRC SWBio DTP PhD studentship: Rapid prediction of effective targets for novel antimicrobials: an essential signalling network in Burkholderia pseudomallei as a test case

This project is one of a number that are in competition for funding from the South West Biosciences Doctoral Training Partnership (SWBio DTP). The SWBio DTP is a BBSRC-funded PhD training programme in the biosciences, delivered by a consortium comprising the Universities of Bristol (lead), Bath, Cardiff and Exeter and Rothamsted Research. The SWBio DTP projects are designed to provide outstanding interdisciplinary training in a range of topics in Agriculture & Food Security and world-class Bioscience, underpinned by training in mathematics and complexity science. Each project will be supervised by an interdisciplinary team of academic staff and will follow a structured training 4-year PhD model.

Up to 4 fully-funded studentships at the University of Exeter are being offered to start in September 2017. The studentships will provide funding for a stipend (currently £14,296 per annum for 2016-17), research costs and UK/EU tuition fees at Research Council UK rates for 48 months (4 years) for full-time students, pro-rata for part-time students.

Academic Supervisors:

Main supervisor: Dr Steven Porter, University of Exeter
Co-supervisor: Prof Ravi Acharya, University of Bath
Co-supervisor: Prof Rick Titball, University of 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 antimicrobial drugs.

Research Objectives:

1. Show that the sensors work together as a network using interaction assays (two-hybrid 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 multikinase-networks 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.

For more information and details on how to apply, go to http://www.exeter.ac.uk/studying/funding/award/?id=2329