Transcription factor-based biosensors: a molecular-guided approach for natural product engineering.
Transcription factor-based biosensors: a molecular-guided approach for natural product engineering.
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基于转录因子的生物传感器：天然产物工程的分子导向方法。
DOI：
10.1016/j.copbio.2021.01.008
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发表时间：
2021-06
影响因子：
7.7
通讯作者：
Williams GJ
中科院分区：
文献类型：
--
作者：
Mitchler MM;Garcia JM;Montero NE;Williams GJ
天然产物及其衍生物提供了丰富的化学和生物多样性来源；然而，为了提高产量和获得非天然衍生物而对它们的生物合成途径进行传统工程需要精确了解它们的酶促过程。可以利用基于变构转录因子的生物传感器的高通量筛选平台来克服筛选瓶颈，从而能够搜索途径/菌株变体的大型文库。本文描述了基于工程变构转录因子的生物传感器的开发和应用，该传感器能够优化前体可用性、产品滴度和下游产品定制，以推进天然产物生物经济。我们讨论了最近在定制生物传感器设计方面取得的成功，包括基于计算的方法，并展示了我们通过整合无细胞技术和从头蛋白质设计来快速生成生物传感器工具的未来展望。
Natural products and their derivatives offer a rich source of chemical and biological diversity; however, traditional engineering of their biosynthetic pathways to improve yields and access to unnatural derivatives requires a precise understanding of their enzymatic processes. High-throughput screening platforms based on allosteric transcription-factor based biosensors can be leveraged to overcome the screening bottleneck to enable searching through large libraries of pathway/strain variants. Herein, the development and application of engineered allosteric transcription factor-based biosensors is described that enable optimization of precursor availability, product titers, and downstream product tailoring for advancing the natural product bioeconomy. We discuss recent successes for tailoring biosensor design, including computationally-based approaches, and present our future outlook with the integration of cell-free technologies and de novo protein design for rapidly generating biosensor tools.
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