(427g) Leveraging and Contrasting Multiple Approaches to Engineer Phenylalanine Ammonia-Lyase (PAL)

Phenylalanine ammonia-lyases (PALs) deaminate L-phenylalanine to trans-cinnamic acid (tCA) and are widely found associated with secondary metabolism in plants, bacteria, and fungi. Biocatalytic applications for natural product (flavonoid, phenylpropanoid) and fine chemical synthesis (e.g., non-canonical amino acids) has driven the discovery, expression, characterization, and engineering of PALs. More recently, development of PALs for phenylketonuria (PKU) management and cancer therapy has further increased interest in engineering this class of enzymes. While there is a general understanding of how residues in the substrate-binding pocket contribute to specificity and turnover, led by rational mutagenesis studies, there is poor understanding of how distal residues affect function. Directed evolution can identify non-obvious and distal hotspot residues that control enzyme activity and can help expedite protein engineering and basic enzymology.

To enable directed evolution, we developed a growth-coupled high throughput screen (HTS) to identify high-activity variants PALs in E. coli (Mays & Mohan et al. 2020 ChemComm). Independently, Flachbart et al. (ACS Synth. Biol. 2019) reported a biosensor-based HTS to engineer PALs. We assessed the strengths and weaknesses of these two screens individually, and in combination. We found that the growth-based screen was susceptible to false negatives whereas the biosensor-based screen was high susceptible to false positives. We developed a method to suppress cheater enrichment, which included integration of biosensor- and the growth-based screens. Concurrently, we also developed a deep mutational scanning (DMS) workflow to develop a detailed sequence-function landscape of PAL, identifying >70 mutational hotspots. Next, we picked seven sites for comprehensive single and multi-site saturation mutagenesis, and identified several variants with improved activity. Finally, to understand the mechanistic role of key mutations in hyperactive variants, we performed modelling studies (quantum mechanics, molecular dynamics, including metadynamics) and concluded that there are multiple pathways to enhance PAL catalytic activity. In summary, this study demonstrates that different screens for the same enzyme can lead to different evolutionary outcomes. We also demonstrated how a DMS workflow can help identify distal and proximal residues important for activity that can help engineer and characterize enzymes.