Single-molecule detection of alpha-synuclein proteins using nanopores
File(s)
Author(s)
Liu, Yaxian
Type
Thesis
Abstract
Nanopore technology has emerged as a key tool for label-free biosensing at the single-molecule level, showing great promise in analytical and diagnostic applications, particularly for early-stage disease detection. This research focuses on enhancing the sensitivity and specificity of nanopipette-based nanopore sensing using carrier strategies. The goal is to address current limitations and establish nanopores as crucial in early molecular-level disease detection, which could revolutionize diagnostics by providing fast and accurate results essential for effective treatment.
The first project phase successfully utilized a DNA carrier attached to an α-Syn aptamer for specific detection of α-Syn oligomers, key in diagnosing neurodegenerative diseases. This approach overcame challenges in distinguishing similar-sized analytes and facilitated the accurate identification of α-Syn oligomers in amyloid diseases. The study introduced detailed subpeak analysis to understand oligomer size diversity and assembly, proving crucial for understanding these diseases.
Next, the research demonstrated the application of nanopore technology with a molecular carrier in cerebrospinal fluid (CSF) to differentiate Parkinson's Disease (PD) patients from healthy individuals. This was achieved without complex sample preparation, using DNA carrier signal patterns to identify α-Syn aggregation indicative of PD. This correlation between nanopore readings and clinical diagnoses suggests a new marker for monitoring PD progression and could lead to better diagnostics and treatment for α-Syn related disorders.
Additionally, the study explored amyloid protein aggregation, using a real-time, label-free technique to monitor secondary nucleation. By analyzing α-Syn monomers' interactions with preformed seeds, the research provided detailed insights into the nucleation process at the molecular level, highlighting the role of nanoclusters in neurodegenerative diseases.
In summary, this research advances nanopore technology in medical research, offering a new nanopore-based DNA carrier method for accurate α-Syn oligomer detection. This method shows potential for clinical diagnosis and contributes significantly to understanding neurodegenerative diseases, particularly in identifying therapeutic targets.
The first project phase successfully utilized a DNA carrier attached to an α-Syn aptamer for specific detection of α-Syn oligomers, key in diagnosing neurodegenerative diseases. This approach overcame challenges in distinguishing similar-sized analytes and facilitated the accurate identification of α-Syn oligomers in amyloid diseases. The study introduced detailed subpeak analysis to understand oligomer size diversity and assembly, proving crucial for understanding these diseases.
Next, the research demonstrated the application of nanopore technology with a molecular carrier in cerebrospinal fluid (CSF) to differentiate Parkinson's Disease (PD) patients from healthy individuals. This was achieved without complex sample preparation, using DNA carrier signal patterns to identify α-Syn aggregation indicative of PD. This correlation between nanopore readings and clinical diagnoses suggests a new marker for monitoring PD progression and could lead to better diagnostics and treatment for α-Syn related disorders.
Additionally, the study explored amyloid protein aggregation, using a real-time, label-free technique to monitor secondary nucleation. By analyzing α-Syn monomers' interactions with preformed seeds, the research provided detailed insights into the nucleation process at the molecular level, highlighting the role of nanoclusters in neurodegenerative diseases.
In summary, this research advances nanopore technology in medical research, offering a new nanopore-based DNA carrier method for accurate α-Syn oligomer detection. This method shows potential for clinical diagnosis and contributes significantly to understanding neurodegenerative diseases, particularly in identifying therapeutic targets.
Version
Open Access
Date Issued
2023-11
Date Awarded
2024-01
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Edel, Joshua
Ivanov, Aleksandar
Publisher Department
Chemistry
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)