Antibiotic resistance in Mycobacterium tuberculosis: A systematic analysis of the interplay between growth rate and metabolic state

Antibiotic resistance (AMR) is expanding dramatically, and the rate of development of novel therapies targeting drug-tolerant and multi-drug resistant strains is very slow. In particular, tuberculosis accounts for 25% of all deaths associated with AMR. The development of novel antibiotics requires an in depth understanding of the mechanisms through which M. tuberculosis resists antibiotics. One of the most remarkable features of the TB bacillus is its variable growth rate: under optimal lab conditions, MTB can only achieve a doubling time of about 16 hours, whilst in the human host growth rates vary upon the site and stage of infection. This is due to the ability of the microorganism for metabolic reprogramming: Both growth rate and metabolic state have been shown to affect antibiotic efficacy.  

In this project, we will use a combined experimental and multi-omics computational modelling approach to test the hypothesis that bacterial metabolic state more accurately predicts antibiotic lethality than growth rate. The outcome of this work will advance our understanding of novel and fundamental aspects of mycobacterial lifestyle and present new avenues for developing antimicrobial therapeutics against arguably one of the most successful pathogens on the planet.  

This project aims at the development of experimental approaches which uncouple growth and metabolism to determine their relative contribution to antibiotic lethality against Mycobacterium tuberculosis. 

Start date
1 July 2021
Duration
3 years
Application deadline
Funding information
  • Full UK/EU tuition fee covered  
  • Stipend at £15,285 p.a. (2020/21)  
  • RTSG of £1,000 p.a.  
  • Personal Computer (provided by the department)  
Funding source
The University of Surrey, Project-led Studentship Award.
Supervised by

About

Tuberculosis was responsible for 1.5 million deaths in 2019 and accounts for 25% of all deaths associated with antibiotic resistance (AMR). The success rate for treating multi-drug resistant TB averages at a dismal 54% globally and is even worse for patients with extensively drug-resistant strains of the causative agent, Mycobacterium tuberculosis. The global tuberculosis (TB) burden is dire and is likely to worsen because of the Covid-19 pandemic, which is destabilising control measures and threatening to reverse the downward trend in TB deaths.  

The development of novel therapies that target drug-tolerant and multi-drug resistant strains of tuberculosis requires an in depth understanding of the mechanisms through which M. tuberculosis resists antibiotics. Slow growth rate is amongst one of the remarkable features of the TB bacillus as this pathogen can only achieve a maximum growth rate equivalent to a doubling time of about 16 hours in optimal laboratory conditions whilst in the human host growth rates vary upon the site and stage of infection. Metabolic reprogramming also underpins every aspect of M. tuberculosis lifecycle in the human host. Both growth rate and metabolic state of bacteria have been shown to affect antibiotic efficacy. In this project, we will use a combined experimental and multi-omics computational modelling approach to test the hypothesis that bacterial metabolic state more accurately predicts antibiotic lethality than growth rate. The outcome of this work will advance our understanding of novel and fundamental aspects of mycobacterial lifestyle and present new avenues for developing antimicrobial therapeutics against arguably one of the most successful pathogens on the planet.  

Methods and Tools. The student will benefit from training in areas of mycobacteriology, molecular biology, continuous culture techniques including working at containment level 3, and state-of-the-art multi-omics and computational modelling in research groups which have excellent track records.  

Dr Joanna Bacon (Public Health England, PHE) will be an external collaborator and advisor of the project. 

References

López-Agudelo et al. (2020) A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks, PLOS Comp Biol 16(6)e1007533;  

Mackenzie. et al. (2020) Bedaquiline reprograms central metabolism to reveal glycolytic vulnerability in Mycobacterium tuberculosis. Nat Commun 11, 6092. https://doi.org/10.1038/s41467-020-19959-4;   

Toro Navarro et al (2018). An enhanced genome-scale metabolic reconstruction of Streptomyces clavuligerus identifies novel strain improvement strategies. Bioproc. Biosys. Eng. 41:657–669. https://doi.org/10.1007/s00449-018-1900-9. 

Eligibility criteria

Applicants should have a good undergraduate degree or a Master’s level qualification in a relevant discipline.

This studentship is only available to UK/EU applicants.

IELTS requirements: IELTS requirements: 6.5 or above (or equivalent) with 6.0 in each individual category. 

How to apply

To apply for this studentship: 

Firstly apply for the Biosciences and Medicine PhD.   

During your application, please mention your desire to apply to this studentship in order to be considered.   

When the system asks you to add your ‘Research Project’ please copy and paste the project description of the project you wish to apply for. 


Application deadline

Contact details

Claudio Avignone Rossa FRSB
09 AX 01
Telephone: +44 (0)1483 686457
E-mail: C.Avignone-Rossa@surrey.ac.uk
Dany Beste
02 AX 01
Telephone: +44 (0)1483 686785
E-mail: D.Beste@surrey.ac.uk

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