Confocal Raman Imaging of Signaling Molecules in Pseudomonas aeruginosa Bacterial Communities

Raman techniques has been an emerging molecular identification tool in biomedical sciences. Among them, Raman imaging are now used as a powerful analytical platform in disease diagnostics and in the study of biochemical phenomena. Its ability to rapidly and non-invasively generate detailed molecular maps of the sample makes Raman imaging a versatile tool for studying communities of the bacteria Pseudomonas aeruginosa is an opportunistic human pathogen and can be found commonly in the environment, for example in soil and in water. P. aeruginosa is responsible for many infection and disease, such as cystic fibrosis (CF). P. aeruginosa is capable of forming biofilms, compounding its ability to resist antibiotic treatment. Therefore, a comprehensive understanding of bacterial behaviors both spatially and temporally will be really helpful for the overall picture.

Swarm motility, biofilm construction and other physiological behaviors are known to be regulated, in part, by alkyl quinolones (AQs) produced as part of its quorum sensing (QS) system. AQ distributions are very spatially-dependent, and chemically distinct from each other, and are very closely related to bacterial strains, surface growth conditions, and other environmental cues. Approaches such as co-culturing different bacterial strains under various environmental conditions, alternating surface motility rate and biofilm growth conditions, developing a three-dimensional imaging set-up to characterize the aggregation depths in bacterial biofilms are used to provide new methodologies for bacterial studies. In summary, this thesis starts by describing the contributions made in advancing the development and application of confocal Raman imaging in bacterial studies mainly by investigating the molecular features of alkyl quinoline (AQ) signaling molecules used in P. aeruginosa quorum sensing system, showing the potential of confocal Raman imaging to elucidate chemical compositions and structures of heterogeneous biological samples. Finally, this thesis discusses the possibility of doing correlated imaging with other analytical imaging approach to explore the bacterial signal molecules and other metabolites at different scales to further the understanding of bacterial virulence, antibiotic resistance, and complex cellular behaviors.