Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2008. / Includes bibliographical references (leaves 54-55). Also available in electronic version.

Infectious diseases remain a serious threat to human life and health as well as having important economical factor. One way of successful combating diseases is designing the most appropriate treatment plan following the correct diagnosis. Therefore, there is a need for a method combining reproducibility, precision and speed. The aim of this work was to evaluate the potential of micro-Raman spectroscopy for identifying bacteria at different taxonomic levels, strains revealing different antibiotic resistance profiles, and for phylogenetic investigation. The project was based on a selection of bacteria: Staphylococcus aureus (6571, Cowanl), Staphylococcus epidermidis (1457, 9142), Escherichia coli including wild- types (strain B, K12, Top 10), transformants expressing ampicillin and kanamycin resistance (Top10Amp, Top10Kan) and clinical isolates expressing extended-spectrum beta- lactamases (ESBL). Following a precise and detailed protocol, Raman spectra were recorded from bacterial colonies grown overnight on a Colombia Blood Agar. In order to remove background fluorescence, rolling-circle filter procedure was applied. The most critical peaks for differentiation between organisms as well as for characterising each microorganism were determined. The spectral data were analyzed using principal component and cluster analysis techniques. As expected, the degree of separation decreased in the order genus→species→strain. It was determined that DNA/RNA, proteins and amino-acids are responsible for the differentiation between strains on a lower level of similarity with more influence of the constituents of the bacterial envelope between more closely related organisms. Raman spectroscopy was capable of differentiating between susceptible and resistant strains as well as monitoring whether the organism has been grown under antibiotic pressure. Based on triplex PCR, clinical isolates of ESBL strains were assigned to one of the phylogenetic group characterising Esherichia genus and it was revealed that within CTX- M TEM-1 there were two distinct clusters of D and B2 groups. Overall we have demonstrated that the combination of micro-Raman spectroscopy, microbiology and bioinformatics has the potential for the successful discrimination of bacteria species and strains, for the determination of antibiotic resistance profiles and investigating phylogenetic grouping in a clinical environment.

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The use of a handheld Raman analyser for the positive identification of raw materials in a manufacturing pharmaceutical company was evaluated using paracetamol as test raw material to evaluate whether such a system would meet Aspen’s regulatory requirements. The approach involved subjecting the chosen raw material to identification tests under a variety of conditions so as to evaluate robustness, and specificity of the system. Thus, raw material provided by different suppliers, different packages of one manufacturing batch, and raw materials subjected to different storage conditions were evaluated. Specificity was evaluated by deliberately contaminating a sample of paracetamol with either acetanilide, or 4-aminophenol, or both at varying concentration levels. The results obtained from these investigations showed that the handheld Raman analyser can correctly identify the selected raw material (paracetamol) under a wide range of conditions, but could not correctly identify the presence of the selected contaminants at lower concentration levels (< 10 – 20 mass percent). Finally, a cost-benefit analysis was carried out in which a scenario of an existing FTIR-ATR system is used for the analysis of a specific number of raw material samples per year as opposed to a scenario in which a new handheld Raman analyser has to be purchased, set up, and used for the analysis of the same number of raw material samples. This comparison showed that the handheld Raman analyser had a pay-back time of approximately 6 months and gave a return on investment of approximately the same value as the actual purchase cost.

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Abstract Chalcogenide glasses and films are excellent candidates for near-infrared guiding configurations in opto-e]ectronics due to the ir high transmission. Their photosensitivity allows waveguide creation by standard lithography or one- and two-photon writing. The near-infrared Raman spectra of a series of As-S(Se) glasses are analyzed using spectral deconvolution and correlated with the molecular structure. Contributions due to As­ (S,Se)3 pyramjdal subunits as well as homopolar Se-Se and S-S bonds are determined. Photoinduced molecular changes in waveguide structures are probed by Raman scattering employing guided mode excitation. A new approach is demonstrated to optically interrogate composite layers where a chalocogenide waveguide provides the substrate and the guiding layer for a biomolecular film whose Raman spectrum is desired. Hydrophilic chalcogenide surfaces were prepared by exposure to 0 ₂ plasma and characterized by XPS spectroscopy. Thin layers of the photo-active protein bacteriorhodopsin were deposited on As₂S3 waveguides and observed by scanning electron and atomic force microscopy. The evanescent wave excited near-infrared Raman spectrum is measured in-situ providing a molecular probe of the chromophore and the light-adaptedstate. This novel technique offers potential for protein monolayer characterization and bio-sensors.

Chalcogenide glasses (ChG) have shown very promising properties for integrated optical applications at the 1.3 and 1.55 µm optical communication wavelengths due to their transparency in the near-infrared region and high nonlinear Kerr effect. Recent experiments on the ChG system have demonstrated the vast flexibility and potential of these materials in applications as optical memories, switches, and diffractive elements, as well as couplers and self-written planar waveguides. However, to advance these novel applications, it is crucial to identify the structure-property relationship in the glass, in both bulk and film materials. Throughout this research work we used conventional near-infrared (NIR) Raman spectroscopy (e.g. backscattering and 90° geometry) to investigate structure-property relationships in chalcogenide materials. Initially, we conducted a homogeneity study of the bulk glass to analyze the elaboration and processing conditions of these glasses. Furthermore, we investigated the compositional variation of the bulk glass and established a relationship between the Raman spectra, and hence their molecular structure, with the optical properties of the material. When the analysis of the bulk glass was completed, we sent the bulk samples to Laval University in Canada, where the fabrication of the thin films and waveguide structures took place. Right after the film and waveguide samples were created, they were sent back to us, where, once again, we conducted a Raman study to investigate any differences between the films and the bulk glass. In this case, the Raman analysis was conducted using Micro-Raman (backscattering geometry) and Waveguide Raman spectroscopy (90° scattering geometry). Here we demonstrate, for the first time to our knowledge, the use of near-infrared (NIR) waveguide Raman spectroscopy to investigate the microstructure of chalcogenide thin films. This integrated optical technique is extremely powerful in the microstructural analysis of thin film devices due to the combination of good molecular specificity and high sensitivity. The Raman spectra depict microstructural differences between As2S3 films, fibers, and bulk glasses. In the ternary compounds, these microstructural differences are less observable. In chalcogen-rich glasses, the vibrational spectra reveal the preferential formation of homopolar Se-Se and S-S bonds. In those compositions, where Se-Se bonds are observed, high nonlinear optical coefficients have been measured. Near-infrared Raman spectroscopy of photoinduced and annealed structures also allows to identify specific bonding changes which accompany the aging process.

Raman spectroscopy is an extremely versatile technique with molecular sensitivity and fingerprint specificity. However, the translation of this tool into a deployable technology has been stymied by irreproducibility in sample preparation and the lack of complex data analysis tools. In this dissertation, a droplet microfluidic platform was prototyped to address both sample-to-sample variation and to introduce a level of quantitation to surface enhanced Raman spectroscopy (SERS). Shifting the SERS workflow from a cell-to-cell mapping routine to the mapping of tens to hundreds of cells demanded the development of an automated processing tool to perform basic SERS analyses such as baseline correction, peak feature selection, and SERS map generation. The analysis tool was subsequently expanded for use with a multitude of diverse SERS applications. Specifically, a two-dimensional SERS assay for the detection of sialic acid residues on the cell membrane was translated into a live cell assay by utilizing a droplet microfluidic device. Combining single-cell encapsulation with a chamber array to hold and immobilize droplets allowed for the interrogation of hundreds of droplets. Our novel application of computer vision algorithms to SERS maps revealed that sialic sugars on cancer cell membranes are found in small clusters, or islands, and that these islands typically occupy less than 30% of the cell surface area. Employing an opportunistic mindset for the application of the data processing platform, a number of smaller projects were pursued. Biodegradable aliphatic-aromatic copolyesters with varying aromatic content were characterized using Raman spectroscopy and principal component analysis (PCA). The six different samples could successfully be distinguished from one another and the tool was able to identify spectral feature changes resulting from an increasing number of aryl esters. Uniquely, PCA was performed on the 3,125 spectra collected from each sample to investigate point-to-point heterogeneities. A third set of projects evaluated the ability of the data processing tool to calculate spectral ratios in an automated fashion and were exploited for use with nano-pH probes and Rayleigh hot-spot normalization. / Ph. D. / How can we understand the dynamic behavior of the cell membrane? Do certain polymeric structures in biodegradable plastic favor bacterial growth and subsequent degradation? To answer these and other intriguing scientific questions, techniques and technologies must be borrowed from a diverse array of fields and combined with fundamental understanding to create innovative solutions. In this dissertation, a two-dimensional surface enhanced Raman spectroscopy (SERS) assay was translated into a live cell assay by utilizing a droplet microfluidic device. Combining single-cell encapsulation with a chamber array to hold and immobilize droplets allowed for the interrogation of hundreds of droplets. Shifting the SERS workflow from a manual cell-to-cell mapping routine to the mapping of tens to hundreds of cells demanded the development of an automated processing tool to perform basic SERS analyses such as baseline correction, peak feature selection, and SERS map generation. Our novel application of computer vision algorithms to SERS maps was able to reveal that sialic sugars on cancer cell membranes are found in small clusters, or islands, and that these islands typically occupy less than 30% of the cell surface area. With an opportunistic mindset, several smaller projects that combine Raman and SERS with extensive data analysis were also pursued. Biodegradable plastics of varying content were studied with Raman spectroscopy. The aliphatic and aromatic polymeric units within these plastics both contain esters, but it is hypothesized that enzymatic hydrolysis occurs at the units asymmetrically. For each of six different samples, five maps were collected, processed using the analysis tool, and then analyzed using a multivariate analysis toolbox. Principal component analysis (PCA) was used to distinguish the polymers and to identify spectral feature changes resulting from an increasing v number of aryl esters. Uniquely, PCA was performed on the 3,125 spectra collected from each sample to investigate point-to-point heterogeneities. A third set of projects evaluated the ability of the data processing tool to calculate spectral ratios in an automated fashion and it was exploited for use with nano-pH probes and Rayleigh hot-spot normalization