University of Dundee

MRC DTP 4 Year PhD Programme: Bacterial stress sensing and antibiotic action

This project is offered as part of the University of Dundee 4-year MRC DTP Programme “Quantitative and Interdisciplinary approaches to biomedical science”. This PhD programme brings together leading experts from the School of Life Sciences (SLS), the School of Medicine (SoM) and the School of Science and Engineering (SSE) to train the next generation of scientists at the forefront of international science.  The outstanding biomedical research at the University of Dundee was recognised by its very high rankings in REF 2014, with Dundee rated as the top University for Biological Sciences in the UK.  A wide range of projects are available within this programme crossing exceptional strengths in four key areas: Infection and Disease; Responses to Cellular Stresses; Development, Stem Cells and Neurobiology; and Big Data and Translation.  All students on this programme will receive training in computational biology, mathematical biology and statistics to equip with the quantitative skills in tackling complex biological questions.  In the 1st year, students will carry out 3 rotation projects prior to selection of the final PhD project.

Acquired resistance to antimicrobial therapy among pathogenic bacteria is a growing public health threat of critical importance. Pseudomonas aeruginosa is an opportunistic pathogen that is naturally resistant to many antibiotics, and can acquire mutations that increase its resistance even further. P.aeruginosa is one of twelve priority pathogens listed by the World Health Organisation with threats requiring further action [1]. One of the mechanisms by which P. aeruginosa can modulate its resistance to antibiotics is by regulating the expression of several different efflux pumps encoded in its genome. Upregulating expression of the efflux pumps leads to increased antibiotic resistance, as the pumps are able to remove antibiotics from the cell. A major known regulator of the expression levels of efflux pumps is the AmgRS two-component system, which senses “cell envelope stress” that develops in response to the antibiotic treatment [2]. This project will focus on developing a mechanistic understanding of how AmgS, a membrane-embedded protein that is the sensing component of the system, is able to detect cell envelope stress. 

Crystal and NMR structures from the E. coli homolog of AmgS, known as EnvZ, are available. EnvZ has been described as a sensor of osmotic and acid stress. In this project, we will investigate the cell envelope stress sensing mechanisms of EnvZ and AmgS. We will first conduct biomolecular simulations of EnvZ in realistic membrane mixture models and construct a structural model of AmgS. Questions of interest will include: 1) how do EnvZ and AmgS interact with the cytoplasmic membrane; 2) how might these interactions be perturbed by osmotic, acid, or antibiotic-induced cell envelope stress, leading to activation of the sensor; and 3) how do reported activating mutations of AmgS, which confer antibiotic resistance, lead to constitutive activation of the sensor? The hypotheses generated in the simulations can then be tested by generating AmgS mutations and analyzing the activity of the mutant protein in vitro using purified proteins or in vivo in P. aeruginosa. Alternatively, complementary biomolecular simulations of E. coli and P. aeruginosa efflux pumps can be performed (see e.g. [3]). A long-term objective is to contribute insight toward strategies for defeating this mechanism employed by P. aeruginosa to increase its resistance to antibiotics. 

[1] Tacconelli et al., The Lancet Infectious Diseases, 2018. 

[2] Lee et al., PNAS 106, 14570–14575, 2009. 

[3] Fitzpatrick et al., Nature Microbiology, 2017. 

Recent work from the lab can be found in the following references:   


  • Kopec et al., Nature Chemistry, 2018 
  • Bartsch, Llabres et al., Scientific Reports, 2019 
  • Llabres et al., J. Struct. Biol., 2019 


  • Bergkessel et al., Molecular Microbiology, 2019 
  • Basta et al., MBio 2017 
  • Babin, Bergkessel et al., PNAS 2016