4.6 Synthetic yeast for biosensing
Communication with the biological world and the digital represent the
next frontier of synthetic yeast futures. The deployment of yeast for
industrial biosensing has applications across multiple sectors – from
beverages to fermentation-based biomanufacturing (Dixon et al.,
2021a,b). An industrial workflow that can be automated at the cellular
level will reduce the level of process touchpoints (human or
autonomous), and is therefore highly likely to result in more resilient
and less error prone engineering loop (Williams et al., 2016, 2017).
Self-regulating bioindustrial systems may benefit from cellular-level
(or enzyme-level in a free cell system) biosensing solutions (Avalos,
2022; Wahid et al., 2023; Yu, Lei and Nie, 2022). These types of
solutions offload sensing and computational needs from adjunct
monitoring equipment to the actual living system responsible for the
biomanufacturing or fermentation process.
The tools and techniques required for engineering autonomous
biosensor-based control loops into yeast constructs are advancing but
continue to require dedicated pre-commercial problem solving at the
level of basic and applied research questions. One of the key problems
continues to be engineering ligand-binding domains and standardising
biosensor architectures (Leonard and Whitehead, 2022; Pham et al.,
2022). Yeast is the perfect organism to prototype industrial solutions
to this problem set due to the model organism S. cerevisiae’sprincipal usage in commercial scale biotechnology worldwide.
Plug-and-play biosensor architectures built for S. cerevisiae can
capture a large market that will favour first movers. To do this,
however, will require solving the two fundamental problems at play in
biosensor research: the lack of detection domains for every conceivable
target molecule and the lack of a standardised architecture. If these
problems are not amendable to a singular solution, then research will
need to focus on standardising protocols of biosensor deployment, rather
than the architecture itself. For example, a commercial biosensor design
would need to begin with a rational process for proof-of-concept using
Fluorescence Resonance Energy Transfer pairs or glucose dehydrogenase
electron transfer (Zhang et al., 2019; Stolarczyket et al., 2020).
Alternatively, tuneable, modular and orthogonal G-protein-coupled
receptors (GPCRs) (Shaw et al., 2019) represent promising targets for
plug-and-play systems. That same process would then need to link the
biosensor pathway into an autonomous internal pathway optimising a
commercial objective such as increasing product yield or quality.