Authors
Dae-Yeol Ye
Published in
Biotechnology journal. Volume 21. Issue 10. Pages e70328.
Abstract
Microbial cell factory development requires iterative optimization of enzymes, pathway fluxes, and cell traits to achieve efficient and robust production of target chemicals. However, the complexity of intracellular metabolic networks often limits predictable identification and control of engineering targets. Genetically encoded metabolite-responsive RNA biosensors based on aptamer recognition and riboswitch- or ribozyme-mediated regulation have emerged as versatile tools for linking intracellular metabolite levels to measurable or selectable outputs. Their rapid signal transduction, compact genetic architecture, and low metabolic burden make them attractive for high-throughput screening and dynamic regulation. This Review adopts a hierarchical engineering framework that examines RNA biosensor applications across progressively broader levels, from enzyme engineering to pathway-level regulation and host-level cellular trait engineering. We further discuss their molecular organization and technological evolution, including ligand recognition, regulatory coupling, sensor tuning, and computational approaches. Finally, challenges associated with sensor robustness, host dependency, scalability, and translation into production-relevant phenotypes are discussed together with opportunities in cell-free characterization and data-driven design. This hierarchical perspective highlights RNA biosensors as engineering interfaces connecting intracellular sensing with interventions across multiple scales of microbial cell factory engineering.
PMID:
42904563
Bibliographic data and abstract were imported from PubMed on 23 Oct 2026.
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