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Access Type
WSU Access
Date of Award
January 2024
Degree Type
Dissertation
Degree Name
Ph.D.
Department
Chemistry
First Advisor
Thomas H. Linz
Abstract
Extracellular vesicles (EVs) play important roles in intercellular communication by transporting biomolecules to neighboring or distant cells. These vesicles participate in diverse biological processes and have garnered considerable interest in biomarker discovery and therapeutic applications. However, these vesicles exhibit remarkable heterogeneity in their biogenesis, cargo composition, and functional properties. Understanding this heterogeneity is crucial for expanding our knowledge of cellular communication and developing novel disease diagnostic and therapeutic strategies. In this dissertation, two novel microfluidic methods are presented to characterize the heterogeneity of EVs. Thermal Gel Electrophoresis (TGE) utilizes an intricate electrical potential scheme to control a temperature-responsive thermal gel for simple EV manipulation. Under high field conditions, thermal gel barriers are generated, isolating EVs from cells. By applying additional voltage, vesicular and cellular content are simultaneously released for downstream analysis. Investigating the correlation in cargos between cells and EVs may contribute to a better understanding of EV heterogeneity. Base-Stacking Digital-Quantitative-PCR (BS-dqPCR) relies on isolating single EVs using immuno beads and microwell arrays for single EV analysis. Substantial progress in developing a robust BS-dqPCR assay for vesicular cargo quantitation is demonstrated, especially with the successful detection of vesicular miRNA and DNA. Microfabrication and BS-PCR optimization are crucial in improving the limit of detection and sensitivity of the assay. Overall, the research presented here has established a groundwork for comprehensive single EV analysis within heterogenous populations.
Recommended Citation
Mai, Hao Tu, "Development Of Microfluidic Methods For Analyzing Vesicular Content" (2024). Wayne State University Dissertations. 3974.
https://digitalcommons.wayne.edu/oa_dissertations/3974
