Date of Award

2021

Degree Type

Thesis

Degree Name

Doctor of Philosophy in Chemical Engineering

Department

Chemical Engineering

First Advisor

Daniel E. Roxbury

Abstract

Non-covalent hybrids of single-stranded DNA and single-walled carbon nanotubes (DNA-SWCNTs) have demonstrated applications in biomedical imaging and sensing due to their enhanced biocompatibility and photostable, environmentally-responsive near-infrared (NIR) fluorescence. Significant progress has been made in developing robust biological probes based on the sensitive optical properties of SWCNTs, however biological environments introduce complex and dynamic conditions that interact with, and ultimately modulate, their intrinsic properties. These fundamental interactions within biological settings can determine whether a nanomaterial is biocompatible and robust, or cytotoxic and disruptive to biological processes. Thus, a mechanistic understanding of such interactions and their effect on cellular function is crucial to the design of nanoscale technology for biomedical purposes.

In this dissertation, several approaches were applied to study the fundamental interactions which occur at the interface between nanomaterials and biological systems (i.e., at the nano-bio interface). We exploited the optical capabilities of DNA-SWCNTs using spectroscopic and microscopy techniques, most notably via near-infrared fluorescence spectroscopy, hyperspectral fluorescence microscopy, and confocal Raman microscopy. Additionally, we developed an advanced hyperspectral immunofluorescence assay to acquire spectral data directly from fluorescently labeled organelles.

The physical and optical stability of DNA-SWCNTs within a biological environment was first assessed as a function of DNA sequence. Short DNA functionalized SWCNTs exhibited reduced physical and optical stability despite higher uptake and exocytosis rates compared to long DNA sequences in a mammalian cell line. Further analysis in primary human cells revealed irreversible aggregation of DNA-SWCNTs occurred during intracellular processing upon localization to lysosomes, however the DNA sequence was not a factor in these processes. Additionally, a machine learning model was trained to predict subcellular localization using the Raman spectrum of internalized DNA-SWCNTs, enabling endosomal mapping using a single marker. Next, a hyperspectral counting method was developed and applied to accurately quantify endosomal loading, revealing both inter and intra-cellular heterogeneity in SWCNT uptake. Moreover, initially-aggregated DNA-SWCNT dispersions were found to inhibit intracellular accumulation in three distinct cell lines despite equal uptake compared to a singly-disperse sample, further highlighting the complex nature of these interactions. Finally, we established and optimized the first generation of wearable textile biosensors for continuous, wireless monitoring of oxidative stress in wound healing applications.

Available for download on Thursday, January 05, 2023

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