Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France.
Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057 Evry, France.
Curr Opin Biotechnol. 2019 Oct;59:78-84. doi: 10.1016/j.copbio.2019.02.016. Epub 2019 Mar 25.
Transcriptional biosensors allow screening, selection, or dynamic regulation of metabolic pathways, and are, therefore, an enabling technology for faster prototyping of metabolic engineering and sustainable chemistry. Recent advances have been made, allowing for routine use of heterologous transcription factors, and new strategies such as chimeric protein design allow engineers to tap into the reservoir of metabolite-binding proteins. However, extending the sensing scope of biosensors is only the first step, and computational models can help in fine-tuning properties of biosensors for custom-made behavior. Moreover, metabolic engineering is bound to benefit from advances in cell-free expression systems, either for faster prototyping of biosensors or for whole-pathway optimization, making it both a means and an end in biosensor design.
转录生物传感器可用于筛选、选择或动态调节代谢途径,因此是快速进行代谢工程和可持续化学原型设计的使能技术。最近的进展使得异源转录因子的常规使用成为可能,而类似嵌合蛋白设计等新策略则使工程师能够利用代谢物结合蛋白库。然而,扩展生物传感器的传感范围只是第一步,计算模型可以帮助微调生物传感器的特性,以实现定制化行为。此外,无细胞表达系统的进步也将使代谢工程受益,无论是用于更快地进行生物传感器原型设计还是用于整个途径的优化,使其成为生物传感器设计的手段和目的。