Marcuccio, Fabio ORCID: https://orcid.org/0000-0003-4816-2896 (2023) Multifunctional Nanoprobes for Single-Entity Analysis. PhD thesis, University of Leeds.
Abstract
Single-entity measurements enable the determination of the individual responses that contribute to the ensemble response that is observed in a heterogeneous system. Within this thesis, two entities are considered: the mammalian cell for single-cell transcriptomics and the DNA molecule for single-molecule sensing. Single-cell transcriptomics (scRNA-seq) has substantially advanced our understanding of cellular heterogeneity in highly complex systems such as Glioblastoma (GBM), a particularly aggressive brain cancer. However, state-of-the-art methods always require isolation and lysis of the cell under investigation, providing only a snapshot of the cell transcriptional state and omitting the dynamic trajectories triggering state transitions. Similarly, solid-state nanopores have emerged as a leading technology for single-molecule detection and analysis, but low signal-to-noise ratios still limit their widespread use in routine laboratory testing. Within this thesis, glass nanopipettes are used as scanning ion-conductance microscopy (SICM) probes to perform nanobiopsies on single glioblastoma cells, longitudinally, throughout standard therapy, and
as glass nanopores to detect the translocation of single double-stranded DNA (dsDNA) molecules, where the translocation signal is enhanced by the presence of polyethylene glycol (PEG). Results show that the nanobiopsy can be used to probe the transcriptional profile of individual GBM cells longitudinally, over a period of 72 hours, transforming scRNA-seq from an endpoint analysis to a temporal assay. A finite element model of a nanopore based on glass nanopipettes provides a mechanistic understanding of the enhanced detection of single dsDNA molecules arising from the cation-binding properties of PEG. Future work will draw on these findings to develop new high-throughput techniques for single-entity detection and characterisation, towards the ultimate goal of unravelling complex heterogeneous systems to advance personalised medicine and healthcare.
Metadata
Supervisors: | Actis, Paolo and Stead, Lucy |
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Keywords: | Single-cell analysis, next-generation sequencing, transcriptomics, longitudinal transcriptome analysis, RNA-seq, glioblastoma, nanopipette, nanopore, biosensors, PEG, biosensing, finite-element modelling, FEM |
Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Academic unit: | Leeds Institute of Medical Research at St James’s |
Depositing User: | Mr Fabio Marcuccio |
Date Deposited: | 11 May 2023 14:54 |
Last Modified: | 01 Jun 2024 00:06 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:32712 |
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