Date of Award
Summer 2024
Document Type
Open Access Dissertation
Department
Biomedical Engineering
First Advisor
Chang Liu
Abstract
Nanopore sensors have garnered significant attention recently, not only for their groundbreaking advancements in single-molecule DNA sequencing but also for their diverse applications in stochastic sensing, single-molecule chemistry, and protein unfolding. The interaction of single molecules with the nanopore sensing interface leads to characteristic ionic current modulations, reflecting the composition, charge, distribution, structure, and sequence of the translocating molecule. With the electrical resistive pulse nanopore sensing, its single-molecule sensitivity and specificity have opened doors to numerous potential applications in personalized medicine. I will discuss recent advancements in the sensitivity and specificity of personalized medicine using nanopore sensors, focusing on proteomic detection and sequencing. Our novel method synergizes chemical modification with DNA-assisted nanopore sensing to achieve high-sensitivity proteomic detection. Host-guest modified DNAs on gold nanoparticles selectively capture antibodies, while DNA probes translocate through the nanopore, enabling specific signals. We have validated this approach with SARS-CoV-2 biomarkers, highlighting the diagnostic potential of nanopore sensing in personalized medicine. Proteomic detection alone is insufficient for personalized medicine. Given the vital role amino acids play in biological functions, proteomic sequencing also becomes crucial for achieving accurate personalized medicine. Our approach integrates Edman degradation with nanopore sensing, enhancing sequencing specificity by derivatizing the N-terminal amino acid. It is hoped that this work will provide the impetus and roadmap for the development of innovative solutions for personalized medicine.
Rights
© 2024, Zehui Zhang
Recommended Citation
Zhang, Z.(2024). Enabling Novel Nanopore Sensing Approaches for Personalized Medicine Through Chemical Modifications to Analytes. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/8014