UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item MULTI-DIMENSIONAL ANALYSIS APPROACHES FOR HETEROGENEOUS SINGLE-CELL DATA(2018) Shen, Yang; Losert, Wolfgang; Chemical Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Improvements in experimental techniques have led to an explosion of information in biology research. The increasing number of measurements comes with challenges in analyzing resulting data, as well as opportunities to obtain deeper insights of biological systems. Conventional average based methods are unfit to analyze high dimensional datasets since they fail to take full advantage of such rich information. More importantly, they are not able to capture the heterogeneity that is prevalent in biological systems. Sophisticated algorithms that are able to utilize all available measurements simultaneously are hence emerging rapidly. These algorithms excel at making full use of information within datasets and revealing detailed heterogeneity. However, there are several important disadvantages of existing algorithms. First, specific knowledge in statistics or machine learning is required to appropriately interpret and tune parameters in these algorithms for future use. This may result in misusage and misinterpretation. Second, using all measurements with equal weighting runs the risk of noise contamination. In addition, information overload has become more common in biology research, with a large volume of irrelevant measurements. Third, regardless of the quality of measurements, analysis methods that simultaneously use a large number of measurements need to avoid the “curse of dimensionality”, which warns that distance estimation and nearest neighbor estimation are not meaningful in high dimensional space. However, most current sophisticated algorithms involve distance estimation and/or nearest neighbor estimation. In this dissertation, my goal is to build analysis methods that are complex enough to capture heterogeneity and at the same time output results in a format that is easy to interpret and familiar to biologists and medical researchers. I tackle the dimension reduction problem by finding not the best subspace but dividing them into multiple subspaces and examine them one by one. I demonstrate my methods with three types of datasets: image-based high-throughput screening data, flow cytometry data, and mass cytometry data. From each dataset, I was able to discover new biological insights as well as re-validate well-established findings with my methods.Item Probing the Internalization Mechanism of a Bacteriophage-encoded Endolysin that can Lyse Extracellular and Intracellular Streptococci(2013) Shen, Yang; Nelson, Daniel C; Molecular and Cell Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Bacteriophage-encoded peptidoglycan hydrolases, or endolysins, have been investigated as an alternative to antimicrobials due to their ability to lyse the bacterial cell wall upon contact. However, pathogens are often able to invade epithelial cells where they can repopulate the mucosal surface after antibiotic or endolysin prophylaxis. Thus, there is growing interest in endolysins that can be engineered, or inherently possess, a capacity to internalize in eukaryotic cells such that they can target extracellular and intracellular pathogens. Previously, one streptococcal specific endolysin, PlyC, was shown to control group A Streptococcus localized on mucosal surfaces as well as infected tissues. To further evaluate the therapeutic potential of PlyC, a streptococci/human epithelial cell co-culture model was established to differentiate extracellular vs. intracellular bacteriolytic activity. We found that a single dose (50 μg/ml) of PlyC was able to decrease intracellular streptococci by 96% compared to controls, as well as prevented the host epithelial cells death. In addition, the internalization and co-localization of PlyC with intracellular streptococci was captured by confocal laser scanning microscopy. Further studies revealed the PlyC binding domain alone, termed PlyCB, with a highly positive-charged surface, was responsible for entry into epithelial cells. By applying site-directed mutagenesis, several positive residues (Lys-23, Lys-59, Arg-66 and Lys-70&71) of PlyCB were shown to mediate internalization. We then biochemically demonstrated that PlyCB directly and specifically bound to phosphatidic acid, phosphatidylserine and phosphatidylinositol through a phospholipid screening assay. Computational modeling suggests that two cationic residues, Lys-59 and Arg-66, form a pocket to help secure the interaction between PlyC and specific phospholipids. Internalization of PlyC was found to be via caveolae-mediated endocytosis in an energy-dependent process with the subsequent intracellular trafficking of PlyC regulated by the PI3K pathway. To the best of our knowledge, PlyC is the first endolysin reported that can penetrate through the eukaryotic lipid membrane and retain biological binding and lytic activity against streptococci in the intracellular niche.