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Developing Methods for Discovering Non-Natural and pH Switching Aptamers


Molecular recognition of disease biomarkers is essential for the detection, monitoring, and treatment of disease. Antibodies, which detect target antigens, have enabled the rapid growth of molecular detection assays and targeted therapies. Despite this, antibodies remain time- and cost-intensive to produce and often have severe limitations in specificity and reproducibility. Aptamers, single stranded DNA or RNA affinity reagents, are a promising alternative. Aptamers are produced in vitro, and they can be chemically synthesized reliably. However, traditional aptamer discovery methods suffer from low enrichment of high affinity aptamers, and aptamer selections frequently fail or yield poor aptamers. Most methods are also constrained by the limited chemical diversity of natural DNA, limiting targets to those with affinity to DNA. Additionally, traditional methods isolate aptamers based only on binding affinity, and it is difficult to generate aptamers with desired functions beyond binding.

Our lab has developed a method called particle display that uses high-throughput, quantitative screening to efficiently isolate high affinity aptamers. Here, we discuss three projects that build on this method to address critical limitations of existing aptamer discovery methods. First, we used this platform to identify an aptamer for p32, a tumor biomarker, with low nanomolar affinity. Next, we extended this method to screen for non-natural DNA aptamers, expanding the chemical diversity of DNA without complex synthesis or polymerase engineering. We generated a mannose-modified DNA aptamer with high affinity and specificity to its target, concanavalin A. Finally, we developed a method to generate pH switching aptamers, for potential use in drug delivery or intracellular sensing. A streptavidin aptamer with pH dependent binding was discovered, and its pH active domain was identified. Together, these methods enable the development of highly functional aptamers for the detection of important biological targets.

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