Measuring chemicals with biology : engineering genetic biosensors for chemical analysis




d'Oelsnitz, Simon

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Nature has evolved incredibly efficient and sustainable technology over millions of years, and we are just now learning how to reprogram it for our needs. In the past century this has been manifested in our ability to create proteins for breaking down and building up chemicals. Common laundry detergents contain a cocktail of enzymes for removing lipids, starches, and sugars from textiles. The pharmaceutical industry is embracing enzymes for more efficient drug synthesis. We are already adopting nature’s solution for chemical manipulation. The next frontier will involve adopting nature’s solution to chemical measurement. All living organisms use proteins, or genetic biosensors, to sense and respond to chemical cues. In the past two decades these natural biosensors have been repurposed for monitoring biomarkers, detecting chemical threats, and screening for improved catalysts. However, just as with enzymes, biosensors from nature oftentimes must be tailored for a desired application. This thesis describes novel methods for engineering genetic biosensors, as well as demonstrations of applications enabled by them, over three independent studies. In the first study, a new evolutionary approach to genetic biosensor design is described and subsequently used to create a series of highly specific sensors for five therapeutic alkaloids. One of these sensors is then used to rapidly evolve a plant methyltransferase enzyme capable of producing tetrahydropapaverine, an immediate precursor to four FDA-approved drugs. Next, the same evolutionary approach is used to create a generalist biosensor responsive to a wide range of otherwise intractable monoterpenes that are commonly used in the fragrance, flavor, cosmetic, and pharmaceutical industries. Finally, the last study describes two separate genetic biosensors engineered to monitor the incorporation of the noncanonical amino acids selenocysteine and L-DOPA. The utility of these sensors is then demonstrated by measuring the incorporation efficiency of thousands of seleno-competent bacterial strains and hundreds of L-DOPA aminoacyl-tRNA synthetases in hours, which would otherwise require months using traditional equipment. Scaling the approaches described herein will facilitate the industrialization of genetic biosensors for next- generation chemical analysis.


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