This thesis focuses on the optimization of surface enhanced Raman for bacteria detection. Many factors influence the outgoing Raman signal in SERS. Coating the nanoparticles used in SERS with a capping agent is one way to enhance the Raman signal. Capping agents can play a significant role in the interaction between the nanoparticles and the bacteria, in turn contributing to the detection of pathogens. To understand the potential of optimizing the capping agent for gold nanoparticles in SERS detection of bacteria, three capping agents — thioglucose (which was not applied previously for the SERS analysis of bacteria), polyvinylpyrrolidone (PVP), and citrate — were tested for their ability to improve species identification and Staphylococcus aureus strain discrimination. The generated samples were run under a dark-field microscopy integrated SERS setup. Upon discriminant analysis, the collected dataset showed that thioglucose and citrate performed well in species identification. However, thioglucose performed better than citrate and PVP in strain discrimination because of its strong ability to integrate with nucleic acid components inside the bacteria cells.
The second experiment explored if SERS can be used to diagnose periprosthetic joint infections (PJI) in shoulder tissue sample. Since the application of SERS on tissue for diagnostic purposes is novel, both ex-situ and in-situ gold nanoparticles were tested. For the in-situ gold nanoparticle integration into tissue samples, the UV reduction method was applied on the samples to generate gold nanoparticles inside the tissues. Multiple conditions were applied on the tissue samples controlling the UV power and UV exposure time. The samples were run in the same dark-field integrated Raman setup initially. The collected data showed that the in-situ gold nanoparticle integration into the shoulder tissue samples through the UV reduction method was successful and has potential. However, the optimum SERS condition could not be confirmed from this analysis due to the high variation of the Raman signal from one tissue sample to the other which generated inconsistent results even in the same applied condition. This suggested that distribution of gold nanoparticle integrated to the tissue was uneven, and thus affected the consistency of the outcomes from the process. Dark field SERS setup was then modified, and a scanning microscope part was incorporated to the system. Rigorous analysis of the SERS spectra from the scanned image and the Raman band assignment of these spectra showed that region high in collagen and protein can provide strong SERS signal. Therefore, to decide on the optimum SERS condition for PJI diagnosis by SERS, scanned image spectra from samples should be obtained. The comparison of all averaged spectra calculated from the highest Raman integral spectra acquired for each condition can point out to the optimum SERS condition. Besides, the relevant band assignment of each spectrum can provide information to understand the mechanism of SERS on shoulder tissue samples.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/43783 |
| Date | 14 July 2022 |
| Creators | Deb, Mahamaya |
| Contributors | Anis, Hanan |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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