Cirino, Patrick C.2021-07-152021-07-15December 22015-12December 2Portions of this document appear in: Gredell, Joseph A., Christopher S. Frei, and Patrick C. Cirino. "Protein and RNA engineering to customize microbial molecular reporting." Biotechnology journal 7, no. 4 (2012): 477-499.https://hdl.handle.net/10657/7876Humans have developed an overwhelming dependence on synthetic materials, which are often costly and environmentally harmful. Over the past decade, there has been a boom in biotechnology, with one emphasis on engaging easily manipulated microorganisms for relatively inexpensive industrial scale production of pharmaceuticals, polymers, and fuels. This challenging field of research offers invaluable benefits to society and the environment. Rapid and precise screening of large libraries of genetically altered microorganisms for enhanced molecule production is a powerful approach to developing such “microbial factories.” Unfortunately, the lack of readily available high-throughput screening techniques inhibits our ability to quickly engineer microorganisms. This limitation is addressed here using engineered whole-cell molecular biosensors based on a family of proteins known as transcriptional regulatory proteins (TRPs). The natural role of many TRPs is to link molecule recognition with gene expression, making them ideal candidates for engineering endogenous molecule biosensors. Through powerful approaches such as directed evolution, TRPs can be altered to recognize targeted value–added molecules and their precursors. Upon recognition of the target molecule, the TRP activates expression of genes with an easily measureable phenotype (e.g., luminescence, cell growth, fluorescence). In the present study, we sought to (i) improve the current screening strategies of TRP libraries, (ii) investigate residue relationships governing the recognition and response of a TRP, and (iii) isolate novel whole-cell biosensors based on the TRP platform. High-throughput screening techniques for isolating functional clones from large genetic libraries ( > 106 mutants) is pivotal to the continued success of engineering microbial factories. Here, we applied fluorescence-activated cell sorting (FACS) combined with antibiotic selections to dramatically improve the throughput of screening large libraries of AraC, an Escherichia coli native TRP. After residue characterization and screening optimization, several functional AraC variants were isolated with desirable specificity and sensitivity toward target molecules, vanillin and salicylate. As we continue to characterize new biosensors and optimize their design process, the limits of TRP molecule recognition are pushed further, thus allowing us to overcome the restraints imposed by natural TRPs and offering sustainable solutions to engineering microbial factories.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).High-throughput screening, FACS, Protein Engineering, transcriptional regulatory proteins2021-07-15Thesisborn digital