National Key Research and Development Program of China (No. 2018YFA0900300), National Natural Science Foundation of China (Nos. 21978071, U1932141), Technical Innovation Special Fund of Hubei Province, China (Nos. 2019AHB055, 2018ACA149), Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang (No. 2018R01014).
The development and implement of microbial chassis cells can provide excellent cell factories for diverse industrial applications, which help achieve the goal of environmental protection and sustainable bioeconomy. The synthetic biology strategy of Design-Build-Test-Learn (DBTL) plays a crucial role on rational and/or semi-rational construction or modification of chassis cells to achieve the goals of “Building to Understand” and “Building for Applications”. In this review, we briefly comment on the technical development of the DBTL cycle and the research progress of a few model microorganisms. We mainly focuse on non-model bacterial cell factories with potential industrial applications, which possess unique physiological and biochemical characteristics, capabilities of utilizing one-carbon compounds or of producing platform compounds efficiently. We also propose strategies for the efficient and effective construction and application of synthetic microbial cell factories securely in the synthetic biology era, which are to discover and integrate the advantages of model and non-model industrial microorganisms, to develop and deploy intelligent automated equipment for cost-effective high-throughput screening and characterization of chassis cells as well as big-data platforms for storing, retrieving, analyzing, simulating, integrating, and visualizing omics datasets at both molecular and phenotypic levels, so that we can build both high-quality digital cell models and optimized chassis cells to guide the rational design and construction of microbial cell factories for diverse industrial applications.
杨永富,耿碧男,宋皓月,胡蜜蜜,何桥宁,陈守文,白凤武,杨世辉. 合成生物学时代基于非模式细菌的工业底盘细胞研究现状与展望[J]. Chinese Journal of Biotechnology, 2021, 37(3): 874-910
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