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|Title:||Development of Raman spectroscopy for biological sample analysis||Authors:||Chen, Keren||Keywords:||DRNTU::Engineering::Chemical engineering::Biochemical engineering||Issue Date:||2017||Source:||Chen, K. (2017). Development of Raman spectroscopy for biological sample analysis. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||This dissertation presents a series of studies in the development of Raman spectroscopy and surface enhanced Raman spectroscopy (SERS) techniques in biological sample analysis, particularly for the characterization of cells and tissues and biomarker detection. First, the background in the target applications and currently available methods are introduced. Spontaneous Raman spectroscopy, surface enhanced Raman spectroscopy and the associated methodology are described to establish the context for the development of more advanced methods in the subsequent chapters. Spontaneous Raman spectroscopy was first applied in the discrimination of neural stem cells and their lineages, to guide the fundamental research for neural stem cell therapy for neurological diseases. Spontaneous Raman spectra were acquired from single cells and then multi-variate analysis was conducted to classify cells and yielded high accuracy. Moreover, we optimized experimental parameters for cell measurements by quantitatively comparing the spectra obtained with various system parameters. Spontaneous Raman spectroscopy was then applied to sample characterization at the tissue level. The feasibility of using spontaneous Raman spectroscopy to diagnose corneal infection caused by fungi was demonstrated. Moreover, it was possible to determine the species of infectious agent. Characterization was enhanced by measuring fungi spores of different species, in which Raman spectra showed significant differences. By use of multi-variate analysis, infected corneas can be easily distinguished from healthy corneas and high accuracy was achieved in the classification of fungi species. To enhance the sensitivity to a particular biomarker for early malaria diagnosis, two methods of SERS were developed to enable the detection of hemozoin, which is a common biomarker for malaria infection, at a range of low concentrations in human blood. In Method 1, silver nanoparticles were simply mixed with preprocessed blood samples; while in Method 2, silver nanoparticles were synthesized inside malaria parasites so that hemozoin would not be diluted prior to measurements. A characteristic SERS peak intensity was used to estimate hemozoin concentration and malaria parasitemia level. The results indicated that Method 2 can achieve ultra-sensitive detection of hemozoin exceeding the sensitivity of the standard method that is based on microscopic examination of Giemsa stained blood smears. It was then realized that Method 2 in the previous study could be employed for the detection of single parasites due to its high sensitivity. By developing a method that enables the association of measured SERS spectra with stained parasites, we demonstrated for the first time that hemozoin from single parasites in the ring stage can be detected. In summary, we have developed a series of spontaneous Raman spectroscopy and SERS techniques and demonstrated their applications in biological sample analysis at different levels. In particular, spontaneous Raman spectroscopy was found highly effective in the differentiation of neural stem cells and their lineages and corneal infection diagnosis. In contrast, SERS can perform ultra-sensitive detection of malaria biomarker for early malaria infection diagnosis. These techniques could be adopted in biological science research and clinical diagnosis once incorporated into a custom built Raman system tailored for particular applications.||URI:||http://hdl.handle.net/10356/72132||DOI:||10.32657/10356/72132||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCBE Theses|
Updated on May 11, 2021
Updated on May 11, 2021
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