酿酒酵母适应性实验室进化工具的最新进展

李祎; 林振泉; 刘子鹤

doi:10.12211/2096-8280.2020-077

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酿酒酵母适应性实验室进化工具的最新进展

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- 酿酒酵母适应性实验室进化工具的最新进展
- Advances in yeast based adaptive laboratory evolution
- 合成生物学 2021年2卷第2期页码：287-301
- 作者机构：
  
  1.北京化工大学生命科学与技术学院，北京 100029
  2.北京化工大学北京软物质科学与工程高精尖创新中心，北京 100029
- 作者简介：
  
  [ "李祎（1994—），男，硕士研究生，研究方向为合成生物学和天然产物。E-mail：2019210667@mail.buct.edu.cn" ]
  [ "林振泉（1987—），男，博士后，研究方向为代谢工程、合成生物学和生物基化学品。E-mail：linzq2@126. com" ]
  [ "刘子鹤（1984—），女，副教授，硕士生导师，研究方向为代谢工程和合成生物学。E-mail：zihe@mail.buct.edu.cn" ]
- 基金信息：
  
  国家重点研发计划“合成生物学”重点专项(2018YFA0900100);中国博士后科学基金第67批面上项目(2020M670115)
- DOI：10.12211/2096-8280.2020-077
  中图分类号： Q-1;Q81
- 收稿：2020-09-16，
  
  修回：2021-02-14，
  
  纸质出版：2021-04-30
- 稿件说明：
移动端阅览
李祎, 林振泉, 刘子鹤. 酿酒酵母适应性实验室进化工具的最新进展[J]. 合成生物学, 2021, 2(2): 287-301

LI Yi, LIN Zhenquan, LIU Zihe. Advances in yeast based adaptive laboratory evolution[J]. Synthetic Biology Journal, 2021, 2(2): 287-301
李祎, 林振泉, 刘子鹤. 酿酒酵母适应性实验室进化工具的最新进展[J]. 合成生物学, 2021, 2(2): 287-301 DOI： 10.12211/2096-8280.2020-077.

LI Yi, LIN Zhenquan, LIU Zihe. Advances in yeast based adaptive laboratory evolution[J]. Synthetic Biology Journal, 2021, 2(2): 287-301 DOI： 10.12211/2096-8280.2020-077.

摘要

酿酒酵母作为重要的模式生物和微生物细胞工厂已广泛用于代谢工程、系统生物学和合成生物学研究。由于微生物系统代谢和调控网络的复杂性，通过人工理性设计及基因扰动难以获得鲁棒性较好的表型，因此进化工程在构建稳定的微生物细胞工厂中发挥着重要作用。微生物适应性实验室进化工程通过模拟自然进化过程，构建大量遗传多样性的突变库，经过筛选可快速获得稳定性状的菌株。随着合成生物学和系统生物学的发展，研究人员开发了多种基因组规模的多位点快速进化工具，并结合计算机辅助进化系统实现了自动化连续进化技术。本综述着重介绍在酿酒酵母中基因组规模的多位点快速进化，包括合成型酿酒酵母基因组重排（SCRaMbLE）、寡核苷酸介导的多位点进化工具（YOGE和eMAGE）和基于CRISPR系统的多位点编辑（CHAnGE、MAGESTIC、Target-AID和yEvolvR）等基因组规模的进化策略的研究；以及自动化连续进化技术（eVOLVER、ICE和ACE等）。利用合成生物学方法通过在基因组水平进行多位点快速编辑或连续进化以产生具有遗传多样性的细胞群体，并在特定的筛选条件下对目标突变株进行富集，进而解析其基因型表型关系，可实现在短期内快速高效识别适应性进化的关键因素和协同作用。最后展望了实验室适应性进化工程与计算机辅助设计、自动化技术有机结合的机遇和在高通量筛选方向的挑战。

Abstract

Saccharomyces cerevisiae

as an eukaryotic model organism and microbial cell factory

has been widely used in metabolic engineering

system biology and synthetic biology. However

due to the limited knowledge of the complex cellular metabolism and inherent regulatory networks

it is difficult to obtain desired phenotypes through rational engineering. Among reported engineering strategies

evolutional engineeri

ng plays an important role in the construction of robust microbial cell factories

particularly when optimizing the whole metabolic or genome-scale network. Adaptive laboratory evolution mimics natural evolution in the laboratory

via

iterative cycles of culture and selection to isolate desirable phenotypes

such as tolerance of high salt concentration

low pH

high temperature condition as well as toxicities from substrate at excess and product accumulated to high titers. With recent advances in genome editing

synthetic biology and systems biology

development in evolution engineering has made great progress

including the computer-aided system and automatic continuous evolution technology. This review focuses on recent technological advances in evolution engineering tools for

S. cerevisiae

. Firstly

recently developed genome evolution strategies are discussed

including the recombinase-based genome-scale engineering system SCRaMbLE (synthetic chromosome rearrangement and modification by loxP-mediated evolution) and SCRaMbLE-in

oligo-mediated YOGE (yeast oligo-mediated genome engineering)

oligo-based genome-scale engineering eMAGE (eukaryotic multiplex automated genome engineering)

CRISPR mediated genome-scale engineering systems CHAnGE (CRISPR/Cas9-and homology-directed-repair-assisted genome-scale engineering)

and MAGESTIC (multiplexed accurate genome editing with short

trackable

integrated cellular barcodes)

Target-AID (target-activation induced cytidine deaminase). Then

yeast-based automated continuous evolution

such as OrthoRep (orthogonal error-prone replication)

ICE (

in vivo

continuous evolution)

eVOLVER (a scalable and automated continuous culture device)

and ACE (automated continuous evolution

pairs OrthoRep with eVOLVER)

are further addressed. These rapid editing strategies at the genome level can generate genetically diverse cell populations to identify key factors and synergies in a short period of time. Finally

we prospect future chal

lenges and opportunities of evolution engineering approaches in advancing yeast-based microbial cell factories. Strategies learned from yeast will also guide the development of other microbial cell factories.

关键词

Keywords

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