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Affinity Chromatography using Concatemeric Functional Nucleic Acids for Biosensing

This thesis describes the use of functional nucleic acid (FNA) superstructures entrapped within monolithic macroporous sol–gel-derived silica for solid-phase flow-based sensing of small molecules and macromolecular proteins. The work described herein overcomes a long-standing issue with entrapment of biomolecule into sol–gel-derived materials; the mesoporous pore morphology required to retain entrapped biomolecules prevents detection of large analytes as these can’t access the entrapped species. It is shown that large DNA superstructures can be produced through rolling circle amplification of a functional nucleic acid, resulting in concatemeric FNA species with dameters of several microns. Such species can be entrapped within macroporous sol-gel derived materials with micron-sized pores with minimal leaching, thus allowing for detection of a wide range of molecules, including biomolecules. Optimal materials for entrapment of FNA superstructures was achieved using a high-throughput material screening method, which minimized biomolecule leaching while maintaining FNA activity. Using an optimized material, concatemeric aptamer superstructures were entrapped within macroporous monolithic columns for flow-based detection of small molecules and proteins, extending the range of analytes that can be analyzed using biohybrid monolithic columns. Preliminary studies on the formation and properties of a DNAzyme superstructure for detection of E. coli detection were also performed, which provided valuable information on factors that must be controlled to allow reproducible fluorescence-based detection of E. coli using the crude intracellular matrix as the target. / Thesis / Master of Science (MSc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/22753
Date14 June 2018
CreatorsKapteyn, Emily
ContributorsBrennan, John, Chemistry and Chemical Biology
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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