Optimization of a Native RNA Purification Method for Application in the Production of RNA-Based Biosensors

Undergraduate Honors Thesis

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Citeable URL: https://scholar.colorado.edu/concern/undergraduate_honors_theses/gt54kq08p

Abstract

Recent developments of genetically encoded RNA-based biosensors have shown great promise for enabling the observation of cellular metabolism on a molecular scale. The design process of these sensors requires the rigorous characterization of candidate RNAs which in turn requires a high level of RNA purity. The common denaturing gel-based RNA purification method has proven to be resource and time inefficient, presenting an issue for biosensor projects which utilize dozens of sensor candidates at a time. A less common RNA purification method which uses unique protein-RNA interactions and protein column purification methods to isolate target RNA is reported to avoid the issues of gel purification, however, it was shown to be less effective when used on large or complex RNAs such as biosensors. Here, we have worked to optimize the column-based RNA purification method for use with RNA-based biosensors. By breaking down the individual steps of biosensor production, including DNA replication and RNA transcription, then reoptimizing them from the ground up, we have gained insight into how various PCR and in vitro transcription reaction conditions affect the ability of a biosensor to be purified using the column-based method while also maximizing its yield. The findings from this study will be used in further optimizations and may eventually be used to inform the development of a biosensor production pipeline.

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