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.