Rapid disease monitoring with resistive-pulse sensing in nanopipettes

Matthews, Lauren (2025). Rapid disease monitoring with resistive-pulse sensing in nanopipettes. University of Birmingham. Ph.D.

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Abstract

Periodontitis, also known as gum disease, is a common inflammatory condition that affects the supporting tissues of the teeth. Without treatment, irreversible damage and tooth loss can occur. The disease can also have a larger impact beyond oral health, such as increasing certain cancer risks and reported links to diabetes. Current diagnostic techniques are qualitative and retrospective, unable to identify biomarkers from the underlying disease processes. There is a growing need for a rapid, quantitative, multiplexed and non-invasive method for effective diagnosis and disease monitoring. One such approach is resistive pulse sensing with nanopores, a single molecule technique with low sample volume requirements. Combined with DNA carriers, containing probe molecules which introduce chemical specificity for target analytes, protein detection and identification is possible. However, analysing complex translocation events requires optimised data analysis workflows, and an understanding of nanopipette transport properties.
In this thesis, sources of noise interference were identified and mitigated in the nanopore set-up, to enable high bandwidth measurements at 100 kHz and above. The effect of the optimisation process was assessed using the root-mean-squared (RMS) noise and the power spectral density of the signal, with alternative equipment and grounding points evaluated. Replacing mains power equipment with battery-powered alternatives, alongside filtering the mains power were unavoidable, were found to be the most effective strategies for reducing noise. Overall, measurement bandwidth was increased from 10 kHz to 100 kHz, with an 82% reduction in RMS noise observed.
The integration of antibodies with DNA carrier structure using the sterically controlled nuclease enhanced DNA assembly method was investigated, to allow for multiplexed assay with greater target analyte applicability. The impact of DNA conjugation to antibodies was determined with a titration enzyme-linked immunosorbent assay method, with only a small decrease in binding ability observed. A 3kbp antibody-DNA conjugate was synthesised, and the structure confirmed with gel electrophoresis imaging. However, attempts to isolate the structure and maintain antibody functionality were unsuccessful.
To aid with interpretation of DNA carrier translocation and assess the suitability of current data analysis methods for high bandwidth measurements, a reference dataset of 4 kbp dsDNA translocation was established. Noise and translocation events were able to be separated temporally, despite low signal-to-noise ratio, and event clustering algorithms distinguished linear and folded DNA conformations. Translocation was seen in both forward and reverse directions, with characteristics following the expected trends, explained by established theoretical models in the literature.
Finally, the focus of this thesis shifted to chemical analysis of the interior sensing region of nanopipettes. A sample preparation method was developed by improving the electrical conductivity with carbon coating, allowing for high resolution imaging with scanning electron microscopy. The interior surface of the nanopipette channel was successfully exposed with focused ion beam milling. Model systems, modified quartz slides, were tested with energy dispersive X-ray spectroscopy (EDX), time-of-flight secondary ion mass spectrometry (ToF-SIMS) and Auger electron spectroscopy (AES), before applying these methods to nanopipette samples. For chemical analysis of nanopipettes, monolayer detection is below the limit of detection for EDX, whilst ToF-SIMS lacked the necessary lateral resolution. AES showed the most promise owing to excellent lateral and depth resolution, but further sample preparation was found to be necessary for charge mitigation purposes.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):