Chemistry & Biochemistry Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2752
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Item HIGH-THROUGHPUT SEQUENCING CHARACTERIZATION OF DNA CYCLIZATION, WITH APPLICATIONS TO DNA LOOPING(2019) Hustedt, Jason Matthew; Kahn, Jason D; Biochemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)DNA flexibility is important both for fundamental biophysics and because DNA flexibility affects DNA packaging and regulation of gene expression through DNA looping. DNA flexibility has been studied with experiments ranging from biochemical ring closure or DNA looping experiments to AFM, crystallography, and tethered particle microscopy. Even so, the flexibility of DNA in vitro and in vivo remains controversial. In an attempt to resolve this controversy, we have developed a high- throughput, internally controlled, comparative ligation methodology using a library constructed of 1023 distinct DNA sequences ranging in length from 119 to 219 base pairs via ligation of pools of synthetic DNA of different lengths and PCR. The design incorporated barcoding for redundant identification of each molecule, allowing for a ligation reaction to be performed on the entire library in one reaction mixture. Two DNA concentrations were used in separate reactions to promote either unimolecular cyclization or bimolecular ligation and thereby explore a wide range of cyclization efficiencies (J factors). Half of each reaction mixture was treated with BAL-31 to destroy non-cyclized molecules. All products were linearized by restriction digestion and Illumina indices were added. The initial library and reaction mixtures were sequenced in a single Illumina MiSeq run. From roughly 15 million assembled reads, over 13 million were identified using software written to identify and sort our sequence library. Each molecule was counted for each condition. From our analysis we see no evidence of extreme bendability at short DNA lengths. At higher DNA concentrations where bimolecular products are produced more rapidly, we see oscillatory behavior as a function of length. In contrast, at lower concentrations where unimolecular products dominate, we observe no helical variation due to the ability for all molecules to cyclize given enough time. In order to determine J factors through cyclization, bimolecular products must also be counted. Given the constraints of this experiment, not all bimolecular products could be observed. Future experimentation can be performed to determine J factors across this size range, the results of which will improve coarse grain modeling of DNA. Extension of this methodology should be applicable to DNA loops anchored by proteins.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 Biochemical characterizations of extracellular vesicles shed by vegetative and sporulating Bacillus subtilis(2015) Kim, Yeji; Fenselau, Catherine; Biochemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Sporulation of Bacilli is a developmental process that provides long-term viability in unfavorable environments. Recently, biogenesis of extracellular vesicles (EVs) from Bacilli has also been reported to participate in various physiological and pathogenic phenomena. In this study, EVs were isolated from vegetative and sporulating Bacillus subtilis cells and characterized using mass spectrometry (MS)-based proteomics, microscopy, and fluorescence spectrophotometry. The microscopic approach demonstrated that both vegetative and sporulating cells produce EVs. In the proteomic analysis, 156 proteins were identified with statistical significance in EVs collected at the vegetative phase and 185 proteins in EVs shed during sporulation. The two EV cargos showed qualitatively and quantitatively different proteome patterns. Sporulation-associated proteins had greater abundances in EVs at the sporulation stage. Additionally, a fusion-like event of EVs with B. subtilis cells was observed by a fluorescence de-quenching assay. Based on these observations, B. subtilis EVs are proposed to support intercellular communication and sporulation.Item Analysis of Intact Proteins in Complex Mixtures(2013) Dhabaria, Avantika; Fenselau, Catherine; Chemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Our goal is to develop an effective work flow for analysis of intact proteins in a complex mixture using the LC-LTQ-Orbitrap XL. Intact protein analysis makes the entire sequence available for characterization, which allows for the identification of isoforms and post translational modifications. We focus on developing a method for top-down proteomics using a high-resolution, high mass accuracy analyzer coupled with bioinformatics tools. The complex mixtures are fractionated using 1-dimensional reversed-phase chromatography and basic reversed- phase, and open tubular electrophoresis. The analysis of intact proteins requires various fragmentation methods such as collisional induced dissociation, high energy collisional dissociation, and electron transfer dissociation. This overall method enables us to analyze intact proteins, providing a better understanding of protein expression levels and post transitional modification information. We have used standard proteins to optimize HPLC conditions and to compare three methods for ion activation and dissociation. Furthermore, we have extended the method to analyze low mass proteins in MCF7 cytosol and in E. coli lysate as a model complex mixture. We have applied this strategy to identify and characterize proteins from extracellular vesicles (EVs) shed by murine myeloid-derived suppressor cells (MDSC). MDSCs suppress both innate and adaptive immune responses to tumor growth and prevent effective immunotherapy. Recently some of the intercellular immunomodulatory effects of MDSC have been shown to be propagated by EVs. Top-down analysis of intact proteins from these EVs was undertaken to identify low mass protein cargo, and to characterize post-translational modifications.