Centre de Biochimie Structurale, INSERM U1054, CNRS UMR5048, University of Montpellier, Montpellier, 34090, France.
Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, 78352, France.
Nat Commun. 2019 Apr 12;10(1):1697. doi: 10.1038/s41467-019-09722-9.
Cell-free transcription-translation systems have great potential for biosensing, yet the range of detectable chemicals is limited. Here we provide a workflow to expand the range of molecules detectable by cell-free biosensors through combining synthetic metabolic cascades with transcription factor-based networks. These hybrid cell-free biosensors have a fast response time, strong signal response, and a high dynamic range. In addition, they are capable of functioning in a variety of complex media, including commercial beverages and human urine, in which they can be used to detect clinically relevant concentrations of small molecules. This work provides a foundation to engineer modular cell-free biosensors tailored for many applications.
无细胞转录-翻译系统在生物传感方面具有巨大的潜力,但可检测的化学物质范围有限。在这里,我们提供了一种工作流程,通过将合成代谢级联与基于转录因子的网络相结合,来扩展无细胞生物传感器可检测的分子范围。这些杂交无细胞生物传感器具有快速的响应时间、强大的信号响应和高动态范围。此外,它们能够在多种复杂的介质中发挥作用,包括商业饮料和人尿,在这些介质中,它们可以用于检测临床相关浓度的小分子。这项工作为工程模块化无细胞生物传感器以适应许多应用提供了基础。