Younger Andrew K D, Dalvie Neil C, Rottinghaus Austin G, Leonard Joshua N
Interdisciplinary Biological Sciences Graduate Program, Northwestern University , Evanston, Illinois 60208, United States.
Department of Chemical and Biological Engineering, Northwestern University , Evanston, Illinois 60208, United States.
ACS Synth Biol. 2017 Feb 17;6(2):311-325. doi: 10.1021/acssynbio.6b00184. Epub 2016 Oct 31.
Efforts to engineer microbial factories have benefitted from mining biological diversity and high throughput synthesis of novel enzymatic pathways, yet screening and optimizing metabolic pathways remain rate-limiting steps. Metabolite-responsive biosensors may help to address these persistent challenges by enabling the monitoring of metabolite levels in individual cells and metabolite-responsive feedback control. We are currently limited to naturally evolved biosensors, which are insufficient for monitoring many metabolites of interest. Thus, a method for engineering novel biosensors would be powerful, yet we lack a generalizable approach that enables the construction of a wide range of biosensors. As a step toward this goal, we here explore several strategies for converting a metabolite-binding protein into a metabolite-responsive transcriptional regulator. By pairing a modular protein design approach with a library of synthetic promoters and applying robust statistical analyses, we identified strategies for engineering biosensor-regulated bacterial promoters and for achieving design-driven improvements of biosensor performance. We demonstrated the feasibility of this strategy by fusing a programmable DNA binding motif (zinc finger module) with a model ligand binding protein (maltose binding protein), to generate a novel biosensor conferring maltose-regulated gene expression. This systematic investigation provides insights that may guide the development of additional novel biosensors for diverse synthetic biology applications.
构建微生物工厂的努力受益于挖掘生物多样性和高通量合成新型酶促途径，但筛选和优化代谢途径仍然是限速步骤。代谢物响应型生物传感器可通过监测单个细胞中的代谢物水平和代谢物响应型反馈控制，帮助应对这些长期存在的挑战。目前我们仅限于自然进化的生物传感器，其不足以监测许多感兴趣的代谢物。因此，一种构建新型生物传感器的方法将很强大，但我们缺乏一种能够构建多种生物传感器的通用方法。作为朝着这个目标迈出的一步，我们在此探索了几种将代谢物结合蛋白转化为代谢物响应型转录调节因子的策略。通过将模块化蛋白质设计方法与合成启动子文库相结合，并应用强大的统计分析，我们确定了构建生物传感器调节的细菌启动子以及实现生物传感器性能设计驱动改进的策略。我们通过将可编程DNA结合基序（锌指模块）与模型配体结合蛋白（麦芽糖结合蛋白）融合，证明了该策略的可行性，从而产生了一种赋予麦芽糖调节基因表达的新型生物传感器。这项系统研究提供的见解可能会指导开发用于各种合成生物学应用的更多新型生物传感器。
