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

Genetically encoded biosensors are
valuable for the optimization
of small-molecule biosynthesis pathways, because they transduce the
production of small-molecule ligands into a readout compatible with
high-throughput screening or selection in vivo. However, engineering
biosensors with appropriate response functions and ligand preferences
remains challenging. Here, we show that the continuous hypermutation
system, OrthoRep, can be effectively applied to evolve biosensors
with a high dynamic range, reprogrammed activity toward desired noncognate
ligands, and proper operational range for coupling to biosynthetic
pathways. In particular, we encoded the allosteric transcriptional
factor, BenM, on OrthoRep such that the propagation of host yeast
cells resulted in BenM’s rapid and continuous diversification.
When these cells were subjected to cycles of culturing and sorting
on BenM activity in the presence and absence of its cognate ligand,
muconic acid, or the noncognate ligand, adipic acid, we obtained multiple
BenM variants that respond to their corresponding ligands. These biosensors
outperform previously engineered BenM-based biosensors by achieving
a substantially greater dynamic range (up to ∼180-fold induction)
and broadened operational range. The expression of select BenM variants
in the presence of a muconic acid biosynthetic pathway demonstrated
sensitive biosensor activation without saturating response, which
should enable pathway and host engineering for higher production of
muconic and adipic acids. Given the streamlined manner in which high-performance
and versatile biosensors were evolved using OrthoRep, this study provides
a template for generating custom biosensors for metabolic pathway
engineering and other biotechnology goals.