Real-time monitoring of the effects of antibiotics on N. gonorrhoeae at the single cell level

Abstract

The sexually transmitted infection gonorrhoea caused by the bacterium Neisseria gonorrhoeae has become resistant to all antibiotics that have been used against it as treatments throughout history. To better preserve the few remaining antibiotics that are effective against this infection, we require rapid and specific antimicrobial susceptibility testing (AST). Reports of extensively drug resistant gonorrhoea are on the rise across the globe. With the ability to prescribe antibiotics for each individual patient rather than using broad spectrum approaches, we may be able to slow down the spread of resistance to allow time for new antibiotics to be tested. Without such actions, the world may soon face untreatable ‘super-gonorrhoea’.

This work focuses on the technique of Sub-Cellular Fluctuation Imaging (SCFI) as an AST with the bacterium N. gonorrhoeae. This method measures nanoscale fluctuations in real time from individual bacterial cells within the evanescent field of a totally internally reflected laser. Previous work with E. coli has established that the fluctuations are an indication of the metabolic state of a bacterium, allowing the user to distinguish between live and dead states. This work initially utilised simulations of E.coli to mimic these nanoscale fluctuations to learn more about the measured signal. Initial experiments were aimed at optimising the SCFI system for use with the smaller diplococci bacterium N. gonorrhoeae. This included deter mining an optimal adhesive, the best laser power and establishing initial readings for a variety of metabolic states. Finally, the SCFI system was tested with different strains of N. gonorrhoeae with antibiotics in seven scenarios as a proof of concept for SCFI as an AST with N. gonorrhoeae. Results indicate that the SCFI fluctuations can distinguish between susceptible and resistant strains, and that results differ between different types of antibiotics. This may indicate differences in the mechanisms of action of antibiotics, and mechanisms of resistance.

Date of Award	3 Oct 2023
Original language	English
Awarding Institution	University of Bristol
Supervisor	Darryl J Hill (Supervisor) & Massimo Antognozzi (Supervisor)