Doctor of Philosophy (PhD), Ohio University, 2025, Electrical Engineering & Computer Science (Engineering and Technology)

The human genome is the blueprint of making a human. It contains all the genetic information needed to build an entire organism and is encoded in the DNA sequence. There are genes in DNA, which provide information for making proteins to perform the functions of the cells. Understanding the genome is essential for learning biological mechanisms, cell developments, and diseases. The 3D genome refers to the three-dimensional structure of the genome within the nucleus. With technologies such as Hi-C and Genome Architecture Mapping, scientists can study the relationship between chromatin interactions and gene regulation. However, there are limited bioinformatics tools that analyze the biological elements in chromatin contacts. In this dissertation, a bioinformatics pipeline that analyzes the feature pairs in chromatin contacts were developed and this pipeline was applied to three case studies. In the first case study pyramidal glutamatergic neurons and dopaminergic neurons were compared. The transcription factor binding sites on the open chromatin region of each cell type were determined, the feature pair analysis pipeline was applied to each cell type, and the transcription factor binding site pairs that have the highest discriminatory power between these two cell types were observed. The results show that the chromatin contacts with these strong discriminatory power transcription factor pairs contain more expressed genes, which are related to cell functions. The second case study compared two techniques that capture three-dimensional chromatin interactions: Genome Architecture Mapping (GAM) and Hi-C. The feature pair analysis pipeline used ChIP-seq data as features. It shows that GAM can capture more active chromatin interactions than Hi-C, while Hi-C captures more inactive chromatin interactions than GAM. The third case study explored early cell development, which analyzed the feature pairs between Embryonic Stem Cells (ESCs) and Extra-embryonic Endoderm (open full item for complete abstract)

Committee: Lonnie Welch (Advisor); David Juedes (Committee Member); Kevin Lee (Committee Member); Chang Liu (Committee Member); Chunmin Lo (Committee Member); Jundong Liu (Committee Member) Subjects: Computer Science

Master of Science (MS), Ohio University, 2021, Biological Sciences (Arts and Sciences)

Parkinson's disease (PD) is a progressive neurodegenerative movement disorder characterized by the loss of dopaminergic (DA) neurons in substantia nigra pars compacta and the formation of Lewy Bodies (LBs), cytoplasmic protein deposits of α-Synuclein (αSyn). In recent years, an intriguing concept of prion-like spreading of pathogenic proteins such as αSyn has emerged. Released αSyn spreads between neurons causing neurodegeneration, but the actual propagation mechanism is still under investigation. In order to test cell-to-cell propagation of αSyn, I investigate αSyn release. In my project, I develop a larval neuromuscular junction (NMJ) model in order to study αSyn release mechanisms. I hypothesize that neuronal activity regulates pathological αSyn release. Thus, using optogenetics to stimulate neurons that co-express αSyn and Channel Rhodopsin (ChR2) in Drosophila melanogaster larvae, I examine αSyn release induced by neuronal depolarization. I use ELISA technique to detect and compare released αSyn levels in the hemolymph of different fly lines. Results show activity-dependent αSyn release. This activity-dependent αSyn release is also influenced by synaptic transmission, mutations, and phosphorylation of αSyn. Hence, αSyn release might be induced in some regions of PD brain in response to excitability, and this αSyn release might underlie the disease progression. Therefore, targeting αSyn release could be further studied in hope of establishing new therapeutic interventions to stop or slow PD pathology.

Committee: Daewoo Lee (Advisor); Corinne Nielsen (Committee Member); Robert Colvin (Committee Member) Subjects: Biology; Neurobiology; Neurosciences

Doctor of Philosophy (PhD), Ohio University, 2019, Biological Sciences (Arts and Sciences)

Learning and memory is an important brain function of animals across phyla, which helps them to collect useful information for survival and adapt to constantly changing environments. In mammals, such as rodents, monkeys, and human beings, the dopaminergic system plays an important role in this process. Dopaminergic neurons in the mesencephalon, especially those in the ventral tegmental area with projections to the prefrontal cortex and the limbic system, have been proved necessary for distinct types of learning and memory. Dopamine receptors, including excitatory D1-like receptors and inhibitory D2-like receptors, are involved in different learning tasks. Compared to mammalian models, Drosophila melanogaster, especially its larva, has a simple nervous system with less redundancy, while retaining the learning ability and a conserved dopaminergic system. Dopaminergic neurons mediate Drosophila olfactory associative learning in both adults and larvae, and D1-like receptor, dDA1, in the mushroom body, the learning center of flies, has been proven important to learning. However, the role of D2-like receptor DD2R in fly learning has not been fully explored. In this study, I explored the expression patterns of DD2R in third instar larval brains using a GFP-tagged DD2R strain, which were confirmed by DD2R-Gal4 lines and DD2R microRNA knockdown experiments. Then I screened dopaminergic drivers marking several neurons or a single neuron, which revealed a one-to-one connection from dopaminergic neurons to corresponding mushroom body compartments. Finally, I investigated that DD2Rs in distinct neurons are necessary for different types of larval olfactory learning. Results from optogenetic activation of specific dopaminergic neurons during learning indicated DD2R achieved its functions via neuronal inhibition. In summary, my study exhibits that DD2R plays an important role in Drosophila larval olfactory associative learning. In the future, studies related to circuit architecture (open full item for complete abstract)

Committee: Daewoo Lee (Advisor); Robert Colvin (Committee Member); Yang Li (Committee Member); Xiaozhuo Chen (Committee Member); William Holmes (Committee Member) Subjects: Neurosciences