About the project
This project will advance the development of Raman spectroscopy and Coherent Anti-stokes Raman Spectroscopy (CARS) as a diagnostic tool for infection and biofilm, and as a research tool to investigate polymicrobial interactions and responses to antibiotic treatment. The project will produce world-leading biofilm images and insights with new technology.
Biofilms have a profound effect on clinical outcomes, yet are difficult to investigate without the use of destructive techniques. Recently, Raman spectroscopy has been used to identify bacterial pathogens and assess the biofilm phenotype in situ. This studentship would further this research, applying it to the issue of antimicrobial resistance conferred by the biofilm.
Machine learning tools will be developed for rapid bacterial identification in multispecies biofilms. Novel methodologies using Raman spectroscopy and Coherent Anti-stokes Raman Spectroscopy (CARS) will be utilised for the generations of biofilm images without the use of chemical labels. The CARS system will allow the generation of world-leading biofilm images, resolved in three dimensions and taken over prolonged time periods. This could examine responses and resistance to antibiotics within biofilms at a previously unseen level.
Using the available medium throughput systems, machine learning tools such as support vector machines could be developed to identify different pathogens rapidly and accurately within a mixed microbial community. They can also provide information about their phenotype, such as stress responses and antibiotic resistance. This has transformative potential for patients and future antimicrobial development, as it will reveal not only when and which antibiotic treatments are effective against biofilms, but the effect that interspecies interactions have on
