生物传感器
生化工程
生物催化
纳米技术
酶
合成生物学
拉伤
化学
代谢工程
计算生物学
定向进化
计算机科学
蛋白质工程
生物技术
固定化酶
生物化学
高通量筛选
生物
作者
Jingyun Zhang,Dan Zheng,Sheena Chan,Matthew W Chang,Chueh Loo Poh
标识
DOI:10.1016/j.copbio.2026.103439
摘要
High-throughput screening (HTS) platforms and automated biofoundries have enabled large-scale experimentation in enzyme and microbial strain engineering. Central to HTS are biosensors and assays, which translate biochemical activities into measurable signals, enabling rapid evaluation of cellular and enzymatic performance. Yet despite advancements in high-throughput infrastructure, the limited availability of robust biosensors or assays and the difficulty of integrating them with HTS, particularly with ultra-HTS, remains a major bottleneck. This review highlights recent progress and challenges in applying biosensors- and assays-enabled HTS for enzyme and strain libraries. We discuss strategies for integrating diverse biosensor types, including transcription factors, G protein-coupled receptors, aptamers, fluorogenic RNAs, riboswitches, and colorimetric assays, with HTS to detect a broad range of metabolites and products. We also explore how biosensor-enabled HTS facilitates data generation for machine learning-guided biocatalyst engineering. Collectively, these advances accelerate biocatalyst discovery and drive the next generation of sustainable biomanufacturing. • Screening is a key bottleneck in biocatalyst engineering. • Advances in biosensors and assays are enabling high-throughput screening (HTS). • New strategies integrate biosensors into HTS to boost enzyme and strain engineering. • Biosensor/assay-enabled HTS facilitates data-driven discovery and machine learning.
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