{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T11:47:03Z","timestamp":1792583223022,"version":"4.5.0"},"reference-count":93,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T00:00:00Z","timestamp":1792540800000},"content-version":"vor","delay-in-days":20,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biotechnology Journal"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>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\u2010responsive RNA biosensors based on aptamer recognition and riboswitch\u2010 or ribozyme\u2010mediated 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\u2010throughput 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\u2010level regulation and host\u2010level 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\u2010relevant phenotypes are discussed together with opportunities in cell\u2010free characterization and data\u2010driven design. This hierarchical perspective highlights RNA biosensors as engineering interfaces connecting intracellular sensing with interventions across multiple scales of microbial cell factory engineering.<\/jats:p>","DOI":"10.1002\/biot.70328","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T11:32:11Z","timestamp":1792582331000},"source":"Crossref","is-referenced-by-count":0,"title":["RNA\u2010Based Biosensors in Microbial Cell Factory Engineering: A Hierarchical Framework From Enzyme to Host\u2010Level Engineering"],"prefix":"10.1002","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-7286-9457","authenticated-orcid":false,"given":"Dae\u2010yeol","family":"Ye","sequence":"first","affiliation":[{"name":"Department of Chemical Biological and Battery Engineering Gachon University  Seongnam Gyeonggi South 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