Date of Final Oral Examination (Defense)
Type of Culminating Activity
Doctor of Philosophy in Materials Science and Engineering
Materials Science and Engineering
Elton Graugnard, Ph.D.
Jeunghoon Lee, Ph.D.
Chris Thachuk, Ph.D.
Eric Hayden, Ph.D.
Currently medical diagnostic methods suffer from the need for skilled labor, bulky, sophisticated and expensive equipment, ideal lab environments and ample time. A point-of-care biosensor can alleviate these problems and allow for more mobile disease detection. To meet this need, researchers have looked to DNA strand displacement networks to perform molecular level computation through a series of DNA strand displacement reactions in which disease associated biomarker inputs can trigger a cascaded signal to produce a readable output downstream in a matter of minutes. Such quick readable outputs require signal amplification. While amplification can be achieved through enzymatic activity, enzymes introduce their own drawbacks. In attempt to eliminate the need for enzymes, entropically driven autocatalytic DNA strand displacement networks are an exclusively DNA approach in which autocatalysts must remain in a metastable state with other network components until activated by an initial catalyst. Premature interaction without an input, known as leakage, can lead to a catalyst release and result in a false signal. Such interactions are counterproductive to reliable disease detection as a biosensor. Toward addressing the leakage problem, I introduce a set of leakage reduction approaches including: hairpin fuels, interfering strands, and steric moieties. These approaches exploit conformational barriers (hairpins), intermittent hybridization barriers (hairpin and interfering strands), and strictly physical barriers (steric moieties). These kinetic barriers resulted in up to 21%, 22% and 1% increases in network performance respectively. This research also reinforced the power of availability as a network design tool and showed that steric moieties are capable of modulating kinetic reaction rates of over three orders of magnitude, demonstrating its immense potential as an important design consideration.
Lysne, Drew, "Kinetic Barriers for Leakage Reduction in DNA Autocatalytic Strand Displacement Networks" (2023). Boise State University Theses and Dissertations. 2089.
Available for download on Thursday, May 01, 2025