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优化无细胞生物传感器以监测酶促生产。

Optimizing Cell-Free Biosensors to Monitor Enzymatic Production.

作者信息

Pandi Amir, Grigoras Ioana, Borkowski Olivier, Faulon Jean-Loup

机构信息

Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay , Jouy-en-Josas 78352 , France.

iSSB Laboratory, Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS , Université Evry, Université Paris-Saclay , 91057 Evry , France.

出版信息

ACS Synth Biol. 2019 Aug 16;8(8):1952-1957. doi: 10.1021/acssynbio.9b00160. Epub 2019 Aug 2.

Abstract

Cell-free systems are promising platforms for rapid and high-throughput prototyping of biological parts in metabolic engineering and synthetic biology. One main limitation of cell-free system applications is the low fold repression of transcriptional repressors. Hence, prokaryotic biosensor development, which mostly relies on repressors, is limited. In this study, we demonstrate how to improve these biosensors in cell-free systems by applying a transcription factor (TF)-doped extract, a preincubation strategy with the TF plasmid, or reinitiation of the cell-free reaction (two-step cell-free reaction). We use the optimized biosensor to sense the enzymatic production of a rare sugar, D-psicose. This work provides a methodology to optimize repressor-based systems in cell-free to further increase the potential of cell-free systems for bioproduction.

摘要

无细胞系统是代谢工程和合成生物学中用于生物部件快速高通量原型设计的有前景的平台。无细胞系统应用的一个主要限制是转录阻遏物的低倍数抑制。因此,主要依赖阻遏物的原核生物传感器的开发受到限制。在本研究中,我们展示了如何通过应用转录因子(TF)掺杂提取物、TF质粒预孵育策略或无细胞反应的重新起始(两步无细胞反应)来改进无细胞系统中的这些生物传感器。我们使用优化后的生物传感器来检测稀有糖D-阿洛酮糖的酶促生产。这项工作提供了一种在无细胞体系中优化基于阻遏物的系统的方法,以进一步提高无细胞系统用于生物生产的潜力。

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