Matching Items (5)
Filtering by

Clear all filters

149796-Thumbnail Image.png
Description
Telomerase is a specialized enzyme that adds telomeric DNA repeats to the chromosome ends to counterbalance the progressive telomere shortening over cell divisions. It has two essential core components, a catalytic telomerase reverse transcriptase protein (TERT), and a telomerase RNA (TR). TERT synthesizes telomeric DNA by reverse transcribing a short

Telomerase is a specialized enzyme that adds telomeric DNA repeats to the chromosome ends to counterbalance the progressive telomere shortening over cell divisions. It has two essential core components, a catalytic telomerase reverse transcriptase protein (TERT), and a telomerase RNA (TR). TERT synthesizes telomeric DNA by reverse transcribing a short template sequence in TR. Unlike TERT, TR is extremely divergent in size, sequence and structure and has only been identified in three evolutionarily distant groups. The lack of knowledge on TR from important model organisms has been a roadblock for vigorous studies on telomerase regulation. To address this issue, a novel in vitro system combining deep-sequencing and bioinformatics search was developed to discover TR from new phylogenetic groups. The system has been validated by the successful identification of TR from echinoderm purple sea urchin Strongylocentrotus purpuratus. The sea urchin TR (spTR) is the first invertebrate TR that has been identified and can serve as a model for understanding how the vertebrate TR evolved with vertebrate-specific traits. By using phylogenetic comparative analysis, the secondary structure of spTR was determined. The spTR secondary structure reveals unique sea urchin specific structure elements as well as homologous structural features shared by TR from other organisms. This study enhanced the understanding of telomerase mechanism and the evolution of telomerase RNP. The system that was used to identity telomerase RNA can be employed for the discovery of other TR as well as the discovery of novel RNA from other RNP complex.
ContributorsLi, Yang (Author) / Chen, Julian Jl (Thesis advisor) / Yan, Hao (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2011
150268-Thumbnail Image.png
Description
A major goal of synthetic biology is to recapitulate emergent properties of life. Despite a significant body of work, a longstanding question that remains to be answered is how such a complex system arose? In this dissertation, synthetic nucleic acid molecules with alternative sugar-phosphate backbones were investigated as potential ancestors

A major goal of synthetic biology is to recapitulate emergent properties of life. Despite a significant body of work, a longstanding question that remains to be answered is how such a complex system arose? In this dissertation, synthetic nucleic acid molecules with alternative sugar-phosphate backbones were investigated as potential ancestors of DNA and RNA. Threose nucleic acid (TNA) is capable of forming stable helical structures with complementary strands of itself and RNA. This provides a plausible mechanism for genetic information transfer between TNA and RNA. Therefore TNA has been proposed as a potential RNA progenitor. Using molecular evolution, functional sequences were isolated from a pool of random TNA molecules. This implicates a possible chemical framework capable of crosstalk between TNA and RNA. Further, this shows that heredity and evolution are not limited to the natural genetic system based on ribofuranosyl nucleic acids. Another alternative genetic system, glycerol nucleic acid (GNA) undergoes intrasystem pairing with superior thermalstability compared to that of DNA. Inspired by this property, I demonstrated a minimal nanostructure composed of both left- and right-handed mirro image GNA. This work suggested that GNA could be useful as promising orthogonal material in structural DNA nanotechnology.
ContributorsZhang, Su (Author) / Chaut, John C (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2011
149296-Thumbnail Image.png
Description
Telomerase is a special reverse transcriptase that extends the linear chromosome termini in eukaryotes. Telomerase is also a unique ribonucleoprotein complex which is composed of the protein component called Telomerase Reverse Transcriptase (TERT) and a telomerase RNA component (TR). The enzyme from most vertebrate species is able to utilize a

Telomerase is a special reverse transcriptase that extends the linear chromosome termini in eukaryotes. Telomerase is also a unique ribonucleoprotein complex which is composed of the protein component called Telomerase Reverse Transcriptase (TERT) and a telomerase RNA component (TR). The enzyme from most vertebrate species is able to utilize a short template sequence within TR to synthesize a long stretch of telomeric DNA, an ability termed "repeat addition processivity". By using human telomerase reconstituted both in vitro (Rabbit Reticulocyte Lysate) and in vivo (293FT cells), I have demonstrated that a conserved motif in the reverse transcriptase domain of the telomerase protein is crucial for telomerase repeat addition processivity and rate. Furthermore, I have designed a "template-free" telomerase to show that RNA/DNA duplex binding is a critical step for telomere repeat synthesis. In an attempt to expand the understanding of vertebrate telomerase, I have studied RNA-protein interactions of telomerase from teleost fish. The teleost fish telomerase RNA (TR) is by far the smallest vertebrate TR identified, providing a valuable model for structural research.
ContributorsXie, Mingyi (Author) / Chen, Julian J.L. (Thesis advisor) / Yan, Hao (Committee member) / Wachter, Rebekka M. (Committee member) / Arizona State University (Publisher)
Created2010
Description

Molecular engineering is an emerging field that aims to create functional devices for modular purposes, particularly bottom-up design of nano-assemblies using mechanical and chemical methods to perform complex tasks. In this study, we present a novel method for constructing an RNA clamp using circularized RNA and a broccoli aptamer for

Molecular engineering is an emerging field that aims to create functional devices for modular purposes, particularly bottom-up design of nano-assemblies using mechanical and chemical methods to perform complex tasks. In this study, we present a novel method for constructing an RNA clamp using circularized RNA and a broccoli aptamer for fluorescence sensing. By designing a circular RNA with the broccoli aptamer and a complementary DNA strand, we created a molecular clamp that can stabilize the aptamer. The broccoli aptamer displays enhanced fluorescence when bound to its ligand, DFHBI-1T. Upon induction with this small molecule, the clamp can exhibit or destroy fluorescence. We demonstrated that we could control the fluorescence of the RNA clamp by introducing different complementary DNA strands, which regulate the level of fluorescence. Additionally, we designed allosteric control by introducing new DNA strands, making the system reversible. We explored the use of mechanical tension to regulate RNA function by attaching a spring-like activity through the RNA clamp to two points on the RNA surface. By adjusting the stiffness of the spring, we could control the tension between the two points and induce reversible conformational changes, effectively turning RNA function on and off. Our approach offers a simple and versatile method for creating RNA clamps with various applications, including RNA detection, regulation, and future nanodevice design. Our findings highlight the crucial role of mechanical forces in regulating RNA function, paving the way for developing new strategies for RNA manipulation, and potentially advancing molecular engineering. Although the current work is ongoing, we provide current progress of both theoretical and experimental calculations based on our findings.

ContributorsJoseph, Joel (Author) / Yan, Hao (Thesis director) / Stephanopoulos, Nicholas (Committee member) / Lapinaite, Audrone (Committee member) / Barrett, The Honors College (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Molecular Sciences (Contributor)
Created2023-05
157564-Thumbnail Image.png
Description
Semi-supervised learning (SSL) is sub-field of statistical machine learning that is useful for problems that involve having only a few labeled instances with predictor (X) and target (Y) information, and abundance of unlabeled instances that only have predictor (X) information. SSL harnesses the target information available in the limited

Semi-supervised learning (SSL) is sub-field of statistical machine learning that is useful for problems that involve having only a few labeled instances with predictor (X) and target (Y) information, and abundance of unlabeled instances that only have predictor (X) information. SSL harnesses the target information available in the limited labeled data, as well as the information in the abundant unlabeled data to build strong predictive models. However, not all the included information is useful. For example, some features may correspond to noise and including them will hurt the predictive model performance. Additionally, some instances may not be as relevant to model building and their inclusion will increase training time and potentially hurt the model performance. The objective of this research is to develop novel SSL models to balance data inclusivity and usability. My dissertation research focuses on applications of SSL in healthcare, driven by problems in brain cancer radiomics, migraine imaging, and Parkinson’s Disease telemonitoring.

The first topic introduces an integration of machine learning (ML) and a mechanistic model (PI) to develop an SSL model applied to predicting cell density of glioblastoma brain cancer using multi-parametric medical images. The proposed ML-PI hybrid model integrates imaging information from unbiopsied regions of the brain as well as underlying biological knowledge from the mechanistic model to predict spatial tumor density in the brain.

The second topic develops a multi-modality imaging-based diagnostic decision support system (MMI-DDS). MMI-DDS consists of modality-wise principal components analysis to incorporate imaging features at different aggregation levels (e.g., voxel-wise, connectivity-based, etc.), a constrained particle swarm optimization (cPSO) feature selection algorithm, and a clinical utility engine that utilizes inverse operators on chosen principal components for white-box classification models.

The final topic develops a new SSL regression model with integrated feature and instance selection called s2SSL (with “s2” referring to selection in two different ways: feature and instance). s2SSL integrates cPSO feature selection and graph-based instance selection to simultaneously choose the optimal features and instances and build accurate models for continuous prediction. s2SSL was applied to smartphone-based telemonitoring of Parkinson’s Disease patients.
ContributorsGaw, Nathan (Author) / Li, Jing (Thesis advisor) / Wu, Teresa (Committee member) / Yan, Hao (Committee member) / Hu, Leland (Committee member) / Arizona State University (Publisher)
Created2019