Progress and prospective of engineering microbial cell factories： from random mutagenesis to customized design in genome scale

doi:10.12211/2096-8208.2020-050

Abstract

Abstract:

As the core of green bio-manufacturing and bioeconomy, microbial cell factories (MCFs) are widely used to produce a variety of chemicals, foods, medicines and fuels. In the early years, isolation and random mutagenesis of natural microbes were time-consuming but widely used for developing well-performed MCFs. With the development of molecular biology and genetic engineering, the advancements in understanding of microbial systems prompted the establishment of metabolic engineering. Nowadays, different MCF-construction strategies in terms of protein, pathway and genome-wide engineering have been well developed based on rational or semi-rational metabolic engineering strategies. However, due to limited biological knowledge, these strategies mainly rely on the iterative cycle of ‘Design-Build-Test-Learning (DBTL)’, usually taking 50—300 person-years and hundreds of millions of dollars to develop a MCF that can meet industrial demands. Combining high-throughput genome editing and phenotype screening and selection technologies, the genome-wide customized engineering allows one to obtain large-scale genotype-phenotype association (GPA) data sets quickly. Based on these results, data science technologies can be further applied to mine a large number of unknown genes or loci associated with the specific phenotypes. This strategy has a wider search scope for genotype (genome-wide) and does not rely on existing biological knowledge (data-driven), thus making it possible to explore phenotypes that could not be achieved by the above mentioned rational/semi-rational strategies and develop MCFs with superior performance more efficiently. This paper reviews general strategies and application cases for the design and construction of MCFs. We will firstly summarize the overview of random mutagenesis strategies, and the history and latest progress in metabolic engineering for the construction of MCFs. Then we discuss the potential of the newly emerging MCF-design and construction paradigm, and the customized design strategies at the whole genome scales. Finally, we conclude with our perspectives on the development of novel strategies for the engineering of MCFs.

Key words: Bio-manufacturing, microbial cell factories, metabolic engineering, genotype-phenotype associations, data-driven

摘要：

微生物细胞工厂（microbial cell factories，MCFs）被广泛用于生产丰富多样的化学品、食品、药品和能源，是绿色生物制造的核心环节。早期主要通过天然微生物的筛选和诱变育种的方式获得高产菌种，然而作为一种“以时间（人力）换水平”的非理性策略，其创制效率极低。随着分子生物学和基因工程研究方法的不断发展，对微生物系统认知和改造能力的进步促使代谢工程学科诞生。基于生物学知识的理性/半理性代谢工程设计和构建策略，目前已发展了从分子、途径到基因组层次不同的MCFs设计和工程化构建策略。本文结合实际案例对MCFs的设计及构建策略进行综述，首先回顾传统诱变育种和代谢工程指导的理性/半理性设计策略，探讨如何突破代谢工程经典框架的限制，实现全基因组水平定制化MCFs的快速构建，最后对这一新的构建范式的未来进行展望。

关键词: 生物制造, 微生物细胞工厂, 代谢工程, 基因型-表型关联, 数据驱动

CLC Number:

Yaomeng YUAN, Xinhui XING, Chong ZHANG. Progress and prospective of engineering microbial cell factories： from random mutagenesis to customized design in genome scale[J]. Synthetic Biology Journal, 2020, 1(6): 656-673.

袁姚梦, 邢新会, 张翀. 微生物细胞工厂的设计构建：从诱变育种到全基因组定制化创制[J]. 合成生物学, 2020, 1(6): 656-673.

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