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Development of RNA Polymerase Biosensors and Their Applications in Synthetic Biology
Protein-protein interactions (PPIs) are crucial for many diverse cellular processes, and dysregulated PPIs are often implicated in disease states. Therefore, monitoring PPIs is critical to understanding underlying biological processes and disease. Many different techniques and tools have been developed to monitor PPIs, including biosensors. Biosensors, which are composed of biological components, contain detection and response elements to facilitate transducing a biochemical signal or event into a detectable output. Certain biosensors with the ability to generate genetic outputs or protein outputs have been utilized for monitoring PPIs and synthetic biology applications including, the generation of synthetic genetic circuits and biosynthetic pathways, diagnostic tools and therapeutics, and sensors for industrial applications. However, the extensive, system-specific engineering and optimization required for many of these biosensors precludes their use in other biosensor designs and applications.
Because of the utility of biosensors to sense, monitor, and impact cellular biology, there is a growing demand in many diverse fields for biosensors that are highly characterized and broadly applicable. My thesis work aimed to generate such a biosensor for PPIs; a sensor that was robust, versatile, and capable of being implemented in orthogonal systems and contexts without the need for extensive re-optimization for each new PPI. By utilizing the T7 RNA polymerase (RNAP) as a scaffold, we developed a new protein fragment complementation assay (PCA)-based biosensor for the detection of PPIs. To optimize the properties of the split T7 RNAP biosensor scaffold, we utilized the directed evolution platform phage assisted continuous evolution (PACE) with a dual positive and negative selection scheme. The resultant split T7 RNAP PCA biosensor scaffold was characterized with multiple PPIs to show its versatility, including light-inducible and small molecule-inducible PPIs; and its orthogonality was demonstrated by testing in both E. coli and mammalian cells. The applicability of the split T7 RNAP biosensor scaffold for novel functions was demonstrated by generating a selection based scheme to interrogate the PPI interface of the KRAS/RAF PPI. Without the need to optimize any component of the split T7 RNAP system, a selection of different RAF variants against KRAS was conducted in order to identify key residues in the interaction interface. Preliminary work with utilizing the split T7 RNAP biosensor scaffold for directed evolution applications was also explored by using stable protein scaffolds, termed antibody mimetics, as starting points to evolve a new PPI partner for the inflammatory bowel disease (IBD) biomarker calprotectin. From the original characterization and these additional applications, we were able to demonstrate how the split T7 RNAP biosensor is a useful tool that can be applied to diverse applications, and should find broad utility in synthetic biology applications
A Phage-Assisted Continuous Selection Approach for Deep Mutational Scanning of Protein-Protein Interactions
Protein-protein interactions (PPIs) are critical for organizing molecules in a cell and mediating signaling pathways. Dysregulation of PPIs are often key drivers of disease. To better understand the biophysical basis of such disease processes – and to potentially target them - it is critical to understand the molecular determinants of PPIs. Deep mutational scanning (DMS) facilitates the acquisition of large amounts of biochemical data by coupling selection with high throughput sequencing (HTS). The challenging and labor-intensive design and optimization of a relevant selection platform for DMS, however, limits the use of powerful directed evolution and selection approaches. To address this limitation, we designed a versatile new phage assisted continuous selection (PACS) system using our proximity-dependent split RNA polymerase (RNAP) biosensors with the aim of greatly simplifying and streamlining the design of a new selection platform for PPIs. After characterization and validation using the model KRAS/RAF PPI, we generated a library of RAF variants and subjected them to PACS and DMS. Our HTS data revealed that amino acid (aa) positions 66, 84, and 89 on RAF, key residues in the KRAS/RAF PPI, are intolerant to mutations. We also identified a subset of residues with broad aa substitution tolerance, aa positions 52, 55, 76, and 79. Due to the plug and play nature of RNAP biosensors, this method can easily be extended to other PPIs. More broadly, this, and other methods under development, supports the application of evolutionary and high-throughput approaches to bear on biochemical problems, moving towards a more comprehensive understanding of sequence-function relationships in proteins