(479f) Engineered Probiotics for Specific Sensing of Aromatic Amino Acids and Neurochemicals | AIChE

(479f) Engineered Probiotics for Specific Sensing of Aromatic Amino Acids and Neurochemicals


Moon, T. S. - Presenter, Washington University in St. Louis
Rottinghaus, A., Washington University In St. Louis
Xi, C., Washington Univeristy In St Louis
Amrofell, M., Washington University in St. Louis
Yi, H., Washington University in St. Louis
Microbes have been engineered to detect metabolites and environmental signals by mining native sensors [1-5] or designing sensors de novo [6]. These modular sensors have the potential to be utilized in probiotic microbes to provide diagnostic information and deliver therapeutics with temporal and geographical precision [7, 8]. However, microbial sensors found in nature often have promiscuity to several structurally similar aromatic amino acids, common neurotransmitters, or neuromodulators, limiting their practical applications. For example, chronically elevated levels of structurally similar phenylalanine and tyrosine are associated with the distinct disorders phenylketonuria and type 2 tyrosinemia, respectively. Extreme phenylethylamine levels have been associated with a variety of psychological disorders, while the presence of tyramine leads to catecholamine release and an increase in blood pressure. Due to such differences in associated diseases and functions, specific sensing is critical for probiotic sensor applications. Despite advances in protein engineering for specific ligand-protein interaction, however, engineering ligand-specific sense-and-respond systems remains challenging, especially when the target ligands are structurally similar and ligand-protein binding should control downstream functions such as gene expression. This is mainly due to the challenge in coupling subtle protein conformational changes caused by binding of similar ligands with differential DNA interactions.

In this work, we first characterized three promiscuous sensors that recognize aromatic metabolites associated with various metabolic and neurological disorders. Common methods of protein engineering require extensive structural knowledge of the proteins or massive library sizes. In contrast, to improve ligand selectivity, we rationally engineered the responsible regulators by identifying and individually mutagenizing specific amino acids. From these three case studies, we show that this simple and generalizable method of protein engineering is effective and time-efficient, requires small library sizes with only a basic understanding of the protein structure, and enables changes in ligand-protein binding specificity while maintaining protein-DNA interaction and thus downstream gene expression control.

In summary, we demonstrate three generalizable approaches, providing the orthogonal DNA-TF binding system with accompanying selectivity changes, the approach to change ligand-TF binding specificity by leveraging TF’s differential multimerization patterns without affecting DNA-TF binding interaction, and a “dual control knob” strategy to improve the specificity and sensitivity of ligand-TF interaction while maintaining DNA-TF binding interaction. Importantly, this work represents a considerable achievement and includes the first ligand-specific and highly-sensitive sensors for phenylalanine, tyrosine, and phenylethylamine. The novel ligand-selective sensors generated in this work will have diverse applications in synthetic biology for developing medically-relevant smart probiotics [7, 8].

[1] DeLorenzo, D. M., Henson, W. R., Moon, T. S., Development of Chemical and Metabolite Sensors for Rhodococcus opacus PD630. ACS Synthetic Biology 2017, 6, 1973–1978.

[2] DeLorenzo, D. M., Moon, T. S., Construction of Genetic Logic Gates Based on the T7 RNA Polymerase Expression System in Rhodococcus opacus PD630. ACS Synthetic Biology 2019, 8, 1921-1930.

[3] Hoynes-O'Connor, A., Shopera, T., Hinman, K., Creamer, J. P., Moon, T. S., Enabling complex genetic circuits to respond to extrinsic environmental signals. Biotechnology and bioengineering 2017, 114, 1626-1631.

[4] Immethun, C. M., DeLorenzo, D. M., Focht, C. M., Gupta, D., et al., Physical, chemical, and metabolic state sensors expand the synthetic biology toolbox for Synechocystis sp. PCC 6803. Biotechnology and bioengineering 2017, 114, 1561-1569.

[5] Immethun, C. M., Ng, K. M., DeLorenzo, D. M., Waldron-Feinstein, B., et al., Oxygen-responsive genetic circuits constructed in synechocystis sp. PCC 6803. Biotechnology and bioengineering 2016, 113, 433-442.

[6] Hoynes-O'Connor, A., Hinman, K., Kirchner, L., Moon, T. S., De novo design of heat-repressible RNA thermosensors in E. coli. Nucleic acids research 2015, 43, 6166-6179.

[7] Amrofell, M. B., Rottinghaus, A. G., Moon, T. S., Engineering microbial diagnostics and therapeutics with smart control. Current opinion in biotechnology 2020, 66, 11-17.

[8] Rottinghaus, A. G., Amrofell, M. B., Moon, T. S., Biosensing in Smart Engineered Probiotics. Biotechnology journal 2020, 15, 1900319.