摘要
随着代谢工程及合成生物学技术的发展,化学品高效生物合成与绿色制造成为可能。高效生物合成体系的设计与构建是绿色生物制造的核心,其理论体系建立及关键技术突破,将为实现绿色生物制造领域高效生产及资源与环境可持续发展提供有力支撑。本文借助代谢途径模块设计的案例,探讨化合物生物合成过程中潜在通用模块设计原则、设计工具,以及基于无细胞蛋白合成体系的代谢模块快速构建及测试的方法,将突破生物合成途径多基因、多模块“设计-构建-测试”(Design-Build-Test cycle,DBT cycle)高效循环迭代的技术瓶颈。结合机器学习方法的应用,将使“设计-构建-测试”向“设计-构建-测试-学习”(Design-Build-Test-Learn cycle,DBTL cycle)进一步延伸,对高效合成模块的“精准-鲁棒性”设计与构建、推动合成生物学科学与技术发展具有重要意义。
Bio-based chemical production has drawn attention regarding the realization of a sustainable society.With the development of metabolic engineering and synthetic biology,it is possible to make more efficient biosynthesis and scale-up commercial production of useful metabolites by metabolic pathway modification.Usually,some microorganisms are utilized as platforms by increasing the expression of desired genes and/or decreasing,that of undesired genes.Precise control of natural metabolism is,however,still challenging due to the complicated regulatory architecture at the levels of transcription,translation,and post-translation.Hence,various strategies of design and construction of biosynthesis modules have been proposed to optimize and expedite the design-build-test cycles of developing biosynthetic system for renewable chemical synthesis in vitro to avoid laborious and expensive ways for theoptimization of metabolism pathway, strain and biocatalysts for each new product. In this review, we discuss thestrategies of modules design and their rapid prototyping based on cell-free protein synthesis for assemblingbiosynthetic pathway in vitro. Biosynthetic modules could be sets of enzymes that catalyze a cascade reaction for aspecific purpose or chemical, containing the conversion of starting materials to intermediary metabolites, biosynthesisof target products from the intermediates, cofactor balance and phosphorylation. Enzymes from distinct sources can becombined to construct desired reaction cascades with fewer biological constraints in one vessel, enabling easierpathway design with high modularity. Multiple modules could then been designed by different groups for differentpurpose with the help of metabolic pathway database,computational design tool and some general module design rules.Cell-free protein synthesis was here utilized to build and rapidly prototype the functionality of biosynthesis pathwayand module. The further application of machine learning methods might also contribute to better “precisionrobustness�
作者
唐士茗
胡纪元
郑穗平
韩双艳
林影
TANG Shiming;HU Jiyuan;ZHENG Suiping;HAN Shuangyan;LIN Ying(School of Biology and Biological Engineering,South China University of Technology,Guangzhou 510006,Guangdong,China)
出处
《合成生物学》
CSCD
2022年第6期1250-1261,共12页
Synthetic Biology Journal
基金
国家重点研发计划(2018YFA0901700)。
