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Evolving Small-Molecule Biosensors with Improved Performance and Reprogrammed Ligand Preference Using OrthoRep.

Alex A Javanpour^1,2, Chang C Liu^1,2,3,4

¹Department of Biomedical Engineering, University of California, Irvine, California 92697, United States.

ACS Synthetic Biology

|October 1, 2021

Summary

Researchers evolved high-performance biosensors using the OrthoRep system for improved metabolic engineering. This method rapidly diversifies proteins, enabling the creation of custom biosensors for optimizing small-molecule production in yeast.

Keywords:

OrthoRep adipic acid biosensors directed evolution metabolic engineering muconic acid

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Area of Science:

Biotechnology
Metabolic Engineering
Synthetic Biology

Background:

Genetically encoded biosensors are crucial for optimizing small-molecule biosynthesis pathways by enabling high-throughput screening.
Engineering biosensors with desired response functions and ligand specificity remains a significant challenge.

Purpose of the Study:

To demonstrate the effectiveness of the OrthoRep continuous hypermutation system for evolving high-performance biosensors.
To engineer biosensors with enhanced dynamic range, reprogrammed ligand activity, and suitable operational ranges for metabolic pathway coupling.

Main Methods:

The OrthoRep system was used to continuously diversify the allosteric transcriptional factor BenM within host yeast cells.
Directed evolution was performed by culturing and sorting cells based on BenM activity in the presence and absence of cognate (muconic acid) and noncognate (adipic acid) ligands.

Main Results:

Multiple BenM variants were evolved that exhibit specific responses to muconic acid and adipic acid.
The evolved biosensors demonstrated a substantially greater dynamic range (up to ~180-fold induction) compared to previously engineered variants.
Selected biosensors showed sensitive activation in the presence of a muconic acid biosynthetic pathway without response saturation.

Conclusions:

The OrthoRep system provides a streamlined and effective method for evolving high-performance, versatile biosensors.
The evolved biosensors are suitable for sensitive activation in metabolic pathway engineering, enabling optimization of small-molecule production.
This study offers a template for generating custom biosensors for metabolic engineering and other biotechnological applications.