酿酒酵母基因组进化的研究进展

doi:10.12211/2096-8280.2020-044

合成生物学 ›› 2020, Vol. 1 ›› Issue (5): 556-569.DOI: 10.12211/2096-8280.2020-044

酿酒酵母基因组进化的研究进展

夏思杨^1,², 江丽红^1,², 蔡谨¹, 黄磊¹, 徐志南¹, 连佳长^1,²

^1.浙江大学化学工程与生物工程学院，生物质化工教育部重点实验室，浙江杭州 310027
^2.浙江大学化学工程与生物工程学院，合成生物学研究中心，浙江杭州 310027

收稿日期:2020-04-08 修回日期:2020-09-28 出版日期:2020-10-31 发布日期:2020-12-03
通讯作者: 蔡谨,连佳长
作者简介:作者简介:夏思杨（1996—），女，硕士研究生。研究方向为基因组进化研究。E-mail：21828174@zju.edu.cn|蔡谨（1960—），男，博士，副教授。研究方向为工业微生物学。E-mail：caij@zju.edu.cn|连佳长（1984—），男，博士，研究员。研究方向为合成生物学。E-mail：jzlian@zju.edu.cn
基金资助:
国家重点研发计划(2018YFA0901800);国家自然科学基金(21808199);浙江省自然科学基金(R20B060006)

Advances in genome evolution of Saccharomyces cerevisiae

Siyang XIA^1,², Lihong JIANG^1,², Jin CAI¹, Lei HUANG¹, Zhinan XU¹, Jiazhang LIAN^1,²

^1.Key Laboratory of Biomass Chemical Engineering of Ministry of Education，College of Chemical and Biological Engineering，Zhejiang University，Hangzhou 310027，Zhejiang，China
^2.Center for Synthetic Biology，College of Chemical and Biological Engineering，Zhejiang University，Hangzhou 310027，Zhejiang，China

Received:2020-04-08 Revised:2020-09-28 Online:2020-10-31 Published:2020-12-03
Contact: Jin CAI,Jiazhang LIAN

摘要/Abstract

摘要：

由于细胞代谢和调控网络的复杂性，尤其是对于多基因调控的复杂性状和遗传工具有限的生物系统而言，基因组进化在微生物细胞工厂的构建中起着至关重要的作用。基因组进化通过人为创造多样化性状以及功能筛选的迭代循环，在实验室中模拟且加速自然进化的过程，从而快速获得满足目标需求的进化突变体。酿酒酵母是代谢工程中重要的底盘细胞，全基因组进化是对其进行系统性改造的最有效合成生物学手段之一。本文总结了基因组进化在构建高效的酿酒酵母细胞工厂中的技术进展和应用，包括基因组改组、转座子插入诱变和全局转录机制工程（gTME）等基于随机突变的非理性基因组进化以及诸如酵母寡核苷酸介导的基因组工程（YOGE），真核基因组多重位点自动改造技术（eMAGE）、RNAi辅助的基因组进化方法（RAGE）以及基于CRISPR体系的基因组规模改造技术（CHAnGE、MAGIC和MAGESTIC）等可示踪的半理性基因组进化，并简要介绍了基因组进化面临的挑战和高通量筛选方法的发展前景。

关键词: 微生物细胞工厂, 基因组进化, 随机突变, 可示踪基因组进化, 酿酒酵母

Abstract:

Due to our limited knowledge of the complicated cellular networks, genome evolution has played critical roles in the construction and optimization of microbial cell factories, especially for those complex traits regulated by multi-genes and for organisms with few genetic engineering tools. Directed genome evolution mimics natural evolution in the laboratory via iterative rounds of genetic diversification and functional screening or selection to isolate evolved mutants with the desirable phenotypes. Genome evolution has been found to be one of the most effective synthetic biology tools for systematic modification and optimization of Saccharomyces cerevisiae, one of the most important chassises in metabolic engineering. This review summarized the advances and applications of genome evolution techniques in the construction and optimization of efficient S. cerevisiae cell factories. Firstly, random mutagenesis based genome evolution strategies, including chemical/physical mutagenesis, genome shuffling, transposon mediated mutagenesis, global transcriptional machinery engineering, recombinase mediated mutagenesis, as well as adaptive laboratory evolution, are introduced. Then, the recently developed trackable genome-scale engineering techniques, including YOGE (yeast oligo-mediated genome engineering), eMAGE (eukaryotic multiplex automated genome engineering), RAGE (RNAi-assisted genome evolution), CHAnGE (CRISPR/Cas9- and homology-directed-repair-assisted genome-scale engineering), MAGIC (multi-functional genome-wide CRISPR system), and MAGESTIC (multiplexed accurate genome editing with short, trackable, integrated cellular barcodes), are discussed in details. In addition, the applications of these irrational and semi-rational genome evolution techniques in engineering yeast cell factories to expand substrate utilization, enhance product formation, and improve cellular properties, are also presented. Finally, the challenges and future directions of genome evolution, particularly when in combination with the high-throughput screening methodologies, are prospected.

Key words: microbial cell factory, genome evolution, random mutagenesis, trackable genome-scale engineering, Saccharomyces cerevisiae

中图分类号:

Q 815

夏思杨, 江丽红, 蔡谨, 黄磊, 徐志南, 连佳长. 酿酒酵母基因组进化的研究进展[J]. 合成生物学, 2020, 1(5): 556-569.

Siyang XIA, Lihong JIANG, Jin CAI, Lei HUANG, Zhinan XU, Jiazhang LIAN. Advances in genome evolution of Saccharomyces cerevisiae[J]. Synthetic Biology Journal, 2020, 1(5): 556-569.

参考文献 63

1	KERKHOVEN E J, LAHTVEE P J, NIELSEN J. Applications of computational modeling in metabolic engineering of yeast [J]. FEMS Yeast Research, 2014, 15(1): 12199.
2	GOFFEAU A, BARRELL B G, BUSSEY H, et al. Life with 6000 genes [J]. Science, 1996, 274(5287): 546, 563-567.
3	HONG Kuk-Ki, NIELSEN J. Metabolic engineering of Saccharomyces cerevisiae: a key cell factory platform for future biorefineries [J]. Cellular and Molecular Life Sciences, 2012, 69(16): 2671-2690.
4	WANG Yajie, YU Xiaowei, ZHAO Huimin. Biosystems design by directed evolution [J]. AIChE Journal, 2020, 66(3): e16716.
5	PATNAIK R. Engineering complex phenotypes in industrial strains [J]. Biotechnology Progress, 2008, 24(1): 38-47.
6	HASHIMOTO S, OGURA M, ARITOMI K, et al. Isolation of auxotrophic mutants of diploid industrial yeast strains after UV mutagenesis [J]. Applied and Environmental Microbiology, 2005, 71(1): 312-319.
7	ROUS C V, SNOW R, KUNKEE R E. Reduction of higher alcohols by fermentation with a leucine-auxotrophic mutant of wine yeast [J]. Journal of the Institute of Brewing, 1983, 89(4): 274-278.
8	BIOT PELLETIER D, MARTIN V J. Evolutionary engineering by genome shuffling [J]. Applied Microbiology and Biotechnology, 2014, 98(9): 3877-3887.
9	ZHANG Yingxin, PERRY K, VINCI V A, et al. Genome shuffling leads to rapid phenotypic improvement in bacteria [J]. Nature, 2002, 415(6872): 644-646.
10	SHI Dongjian, WANG Changlu, WANG Kuiming. Genome shuffling to improve thermotolerance, ethanol tolerance and ethanol productivity of Saccharomyces cerevisiae [J]. Journal of Industrial Microbiology & Biotechnology, 2009, 36(1): 139-147.
11	ZHENG D Q, WU X C, WANG P M, et al. Drug resistance marker-aided genome shuffling to improve acetic acid tolerance in Saccharomyces cerevisiae [J]. Journal of Industrial Microbiology & Biotechnology, 2011, 38(3): 415-422.
12	KUMAR A, SERINGHAUS M, BIERY M C, et al. Large-scale mutagenesis of the yeast genome using a Tn7-derived multipurpose transposon [J]. Genome Research, 2004, 14(10a): 1975-1986.
13	NI Haiying, LAPLAZA J M, JEFFRIES T W. Transposon mutagenesis to improve the growth of recombinant Saccharomyces cerevisiae on D-xylose [J]. Applied and Environmental Microbiology, 2007, 73(7): 2061-2066.
14	ALPER H, MOXLEY J, NEVOIGT E, et al. Engineering yeast transcription machinery for improved ethanol tolerance and production [J]. Science, 2006, 314(5805): 1565-1568.
15	NAGY A. Cre recombinase: the universal reagent for genome tailoring [J]. Genesis, 2000, 26(2): 99-109.
16	TURAN S, BODE J. Site-specific recombinases: from tag-and-target- to tag-and-exchange-based genomic modifications [J]. FASEB Journal, 2011, 25(12): 4088-4107.
17	DYMOND J S, RICHARDSON S M, COOMBES C E, et al. Synthetic chromosome arms function in yeast and generate phenotypic diversity by design [J]. Nature, 2011, 477(7365): 471-476.
18	JIA Bin, WU Yi, LI Bingzhi, et al. Precise control of SCRaMbLE in synthetic haploid and diploid yeast [J]. Nature Communications, 2018, 9(1): 1933.
19	Eun Joong OH, SKERKER J M, KIM Soo Rin, et al. Gene amplification on demand accelerates cellobiose utilization in engineered Saccharomyces cerevisiae [J]. Applied and Environmental Microbiology, 2016, 82(12): 3631-3639.
20	KIM Soo Rin, SKERKER J M, KANG Wei, et al. Rational and evolutionary engineering approaches uncover a small set of genetic changes efficient for rapid xylose fermentation in Saccharomyces cerevisiae [J]. PLoS One, 2013, 8(2): e57048.
21	ENQUIST NEWMAN M, FAUST A M, BRAVO D D, et al. Efficient ethanol production from brown macroalgae sugars by a synthetic yeast platform [J]. Nature, 2014, 505(7482): 239-243.
22	VOORDECKERS K, KOMINEK J, DAS A, et al. Adaptation to high ethanol reveals complex evolutionary pathways [J]. PLoS Genetics, 2015, 11(11): e1005635.
23	GONZÁLEZ-RAMOS D, DE VRIES A R G, GRIJSEELS S S, et al. A new laboratory evolution approach to select for constitutive acetic acid tolerance in Saccharomyces cerevisiae and identification of causal mutations [J]. Biotechnology for Biofuels, 2016, 9: 173.
24	FLETCHER E, FEIZI A, BISSCHOPS M M, et al. Evolutionary engineering reveals divergent paths when yeast is adapted to different acidic environments [J]. Metabolic Engineering, 2017, 39: 19-28.
25	HACISALIHOĞLU B, HOLYAVKIN C, TOPALOĞLU A, et al. Genomic and transcriptomic analysis of a coniferyl aldehyde-resistant Saccharomyces cerevisiae strain obtained by evolutionary engineering [J]. FEMS Yeast Research, 2019, 19(3): foz021.
26	CASPETA L, CHEN Yun, GHIACI P, et al. Altered sterol composition renders yeast thermotolerant [J]. Science, 2014, 346(6205): 75-78.
27	OUD B, MARIS A J VAN, DARAN J M, et al. Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast [J]. FEMS Yeast Research, 2012, 12(2): 183-196.
28	HONG Min Eui, Ki Sung LEE, YU Byung Jo, et al. Identification of gene targets eliciting improved alcohol tolerance in Saccharomyces cerevisiae through inverse metabolic engineering [J]. Journal of Biotechnology, 2010, 149(1/2): 52-59.
29	DICARLO J E, CONLEY A J, PENTTILA M, et al. Yeast oligo-mediated genome engineering (YOGE) [J]. ACS Synthetic Biology, 2013, 2(12): 741-749.
30	BARBIERI E M, MUIR P, AKHUETIE-ONI B O, et al. Precise editing at DNA replication forks enables multiplex genome engineering in eukaryotes [J]. Cell, 2017, 171(6): 1453-1467
31	SI Tong, LUO Yunzi, BAO Zehua, et al. RNAi-assisted genome evolution in Saccharomyces cerevisiae for complex phenotype engineering [J]. ACS Synthetic Biology, 2015, 4(3): 283-291.
32	SI Tong, CHAO Ran, MIN Yuhao, et al. Automated multiplex genome-scale engineering in yeast [J]. Nature Communications, 2017, 8(1): 15187.
33	BAO Zehua, HAMEDIRAD M, XUE Pu, et al. Genome-scale engineering of Saccharomyces cerevisiae with single-nucleotide precision [J]. Nature Biotechnology, 2018, 36(6): 505-508.
34	LIAN Jiazhang, SCHULTZ C, CAO Mingfeng, et al. Multi-functional genome-wide CRISPR system for high throughput genotype-phenotype mapping [J]. Nature Communications, 2019, 10(1): 5794.
35	ROY K R, SMITH J D, VONESCH S C, et al. Multiplexed precision genome editing with trackable genomic barcodes in yeast [J]. Nature Biotechnology, 2018, 36(6): 512-520.
36	WANG H H, ISAACS F J, CARR P A, et al. Programming cells by multiplex genome engineering and accelerated evolution [J]. Nature, 2009, 460(7257): 894-898.
37	PIJKEREN J P VAN, BRITTON R A. High efficiency recombineering in lactic acid bacteria [J]. Nucleic Acids Research, 2012, 40(10): e76.
38	DRINNENBERG I A, WEINBERG D E, XIE K T, et al. RNAi in budding yeast [J]. Science, 2009, 326(5952): 544-550.
39	XIAO Han, ZHAO Huimin. Genome-wide RNAi screen reveals the E3 SUMO-protein ligase gene SIZ1 as a novel determinant of furfural tolerance in Saccharomyces cerevisiae [J]. Biotechnology for Biofuels, 2014, 7(1): 78.
40	BAO Zehua, XIAO Han, LIANG Jing, et al. Homology-integrated CRISPR-Cas (HI-CRISPR) system for one-step multigene disruption in Saccharomyces cerevisiae [J]. ACS Synthetic Biology, 2015, 4(5): 585-594.
41	RUSSA M F LA, QI L S. The new state of the art: Cas9 for gene activation and repression [J]. Molecular and Cellular Biology, 2015, 35(22): 3800-3809.
42	LIAN Jiazhang, HAMEDIRAD M, HU Sumeng, et al. Combinatorial metabolic engineering using an orthogonal tri-functional CRISPR system [J]. Nature Communications, 2017, 8(1): 1688.
43	Suk Jin HA, GALAZKA J M, KIM Soo Rin, et al. Engineered Saccharomyces cerevisiae capable of simultaneous cellobiose and xylose fermentation [J]. Proceedings of the National Academy of Sciences of the United States of America, 2011, 108(2): 504-509.
44	WEI Na, QUARTERMAN J, KIM Soo Rin, et al. Enhanced biofuel production through coupled acetic acid and xylose consumption by engineered yeast [J]. Nature Communications, 2013, 4(1): 2580.
45	WEI Na, Eun Joong OH, MILLION G, et al. Simultaneous utilization of cellobiose, xylose, and acetic acid from lignocellulosic biomass for biofuel production by an engineered yeast platform [J]. ACS Synthetic Biology, 2015, 4(6): 707-713.
46	REYES L H, GOMEZ J M, KAO K C. Improving carotenoids production in yeast via adaptive laboratory evolution [J]. Metabolic Engineering, 2014, 21: 26-33.
47	PATZSCHKE A, STEIGER M G, HOLZ C, et al. Enhanced glutathione production by evolutionary engineering of Saccharomyces cerevisiae strains [J]. Biotechnology Journal, 2015, 10(11): 1719-1726.
48	YU Tao, ZHOU Yongjin J, HUANG Mingtao, et al. Reprogramming yeast metabolism from alcoholic fermentation to lipogenesis [J]. Cell, 2018, 174(6): 1549-1558
49	ZHU Zhiwei, HU Yating, TEIXEIRA P G, et al. Multidimensional engineering of Saccharomyces cerevisiae for efficient synthesis of medium-chain fatty acids [J]. Nature Catalysis, 2020, 3(1): 64-74.
50	WANG Yanfeng, ZHANG Shuxian, LIU Huaqing, et al. Changes and roles of membrane compositions in the adaptation of Saccharomyces cerevisiae to ethanol [J]. Journal of Basic Microbiology, 2015, 55(12): 1417-1426.
51	SNOEK T, PICCA NICOLINO M, BREMT S VAN DEN, et al. Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance [J]. Biotechnology for Biofuels, 2015, 8(1): 32.
52	LING Hua, JUWONO N K P, Wei Suong TEO, et al. Engineering transcription factors to improve tolerance against alkane biofuels in Saccharomyces cerevisiae [J]. Biotechnology for Biofuels, 2015, 8(1): 231.
53	BRENNAN T C, WILLIAMS T C, SCHULZ B L, et al. Evolutionary engineering improves tolerance for replacement jet fuels in Saccharomyces cerevisiae [J]. Applied and Environmental Microbiology, 2015, 81(10): 3316-3325.
54	BRACHER J M, DE HULSTER E, KOSTER C C, et al. Laboratory evolution of a biotin-requiring Saccharomyces cerevisiae strain for full biotin prototrophy and identification of causal mutations [J]. Applied and Environmental Microbiology, 2017, 83(16): e00892-00817.
55	LI Sijin, SI Tong, WANG Meng, et al. Development of a synthetic malonyl-CoA Sensor in Saccharomyces cerevisiae for intracellular metabolite monitoring and genetic screening [J]. ACS Synthetic Biology, 2015, 4(12): 1308-1315.
56	WANG Meng, LI Sijin, ZHAO Huimin. Design and engineering of intracellular-metabolite-sensing/regulation gene circuits in Saccharomyces cerevisiae [J]. Biotechnology and Bioengineering, 2016, 113(1): 206-215.
57	MUKHERJEE K, BHATTACHARYYA S, PERALTA-YAHYA P. GPCR-based chemical biosensors for medium-chain fatty acids [J]. ACS Synthetic Biology, 2015, 4(12): 1261-1269.
58	KIM Hee-Jung, Sura HA, Hee Yoon LEE, et al. ROSics: chemistry and proteomics of cysteine modifications in redox biology [J]. Mass Spectrometry Reviews, 2015, 34(2): 184-208.
59	LEAVITT J M, WAGNER J M, TU C C, et al. Biosensor-enabled directed evolution to improve muconic acid production in Saccharomyces cerevisiae [J]. Biotechnology Journal, 2017, 12(10): 1600687.
60	MAIR P, GIELEN F, HOLLFELDER F. Exploring sequence space in search of functional enzymes using microfluidic droplets [J]. Current Opinion in Chemical Biology, 2017, 37: 137-144.
61	CHEN B, Sungwon LIM, KANNAN A, et al. High-throughput analysis and protein engineering using microcapillary arrays [J]. Nature Chemical Biology, 2016, 12(2): 76-81.
62	LARSEN A C, DUNN M R, HATCH A, et al. A general strategy for expanding polymerase function by droplet microfluidics [J]. Nature Communications, 2016, 7(1): 11235.
63	DORR M, FIBINGER M P, LAST D, et al. Fully automatized high-throughput enzyme library screening using a robotic platform [J]. Biotechnology and Bioengineering, 2016, 113(7): 1421-1432.

[1]	吴玉洁, 刘欣欣, 刘健慧, 杨开广, 随志刚, 张丽华, 张玉奎. 基于高通量液相色谱质谱技术的菌株筛选与关键分子定量分析研究进展[J]. 合成生物学, 2023, 4(5): 1000-1019.
[2]	孙梦楚, 陆亮宇, 申晓林, 孙新晓, 王佳, 袁其朋. 基于荧光检测的高通量筛选技术和装备助力细胞工厂构建[J]. 合成生物学, 2023, 4(5): 947-965.
[3]	高纤云, 牛灵雪, 见妮, 管宁子. 微生物合成生物学在疾病诊疗上的应用进展[J]. 合成生物学, 2023, 4(2): 263-282.
[4]	潘颖佳, 夏思杨, 董昌, 蔡谨, 连佳长. 基因增变器驱动的酿酒酵母基因组连续进化[J]. 合成生物学, 2023, 4(1): 225-240.
[5]	任师超, 孙秋艳, 冯旭东, 李春. 微生物细胞工厂合成五环三萜皂苷类化合物[J]. 合成生物学, 2022, 3(1): 168-183.
[6]	陈久洲, 王钰, 蒲伟, 郑平, 孙际宾. 5-氨基乙酰丙酸生物合成技术的发展及展望[J]. 合成生物学, 2021, 2(6): 1000-1016.
[7]	熊亮斌, 宋璐, 赵云秋, 刘坤, 刘勇军, 王风清, 魏东芝. 甾体化合物绿色生物制造：从生物转化到微生物从头合成[J]. 合成生物学, 2021, 2(6): 942-963.
[8]	郭亮, 高聪, 柳亚迪, 陈修来, 刘立明. 大肠杆菌生产饲用氨基酸的研究进展[J]. 合成生物学, 2021, 2(6): 964-981.
[9]	孙文涛, 张昕哲, 万盛通, 王茹雯, 李春. Ⅱ型细胞色素P450酶氧化β-香树脂醇的选择性调控研究[J]. 合成生物学, 2021, 2(5): 804-814.
[10]	李晓东, 杨成帅, 王平平, 严兴, 周志华. 构建酿酒酵母细胞工厂从头合成倍半萜类化合物α-新丁香三环烯和β-石竹烯[J]. 合成生物学, 2021, 2(5): 792-803.
[11]	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.
[12]	盛月, 张根林. 酵母终止子工程：从机理探索到人工设计[J]. 合成生物学, 2020, 1(6): 709-721.
[13]	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.
[14]	许可, 王靖楠, 李春. 智能抗逆微生物细胞工厂与绿色生物制造[J]. 合成生物学, 2020, 1(4): 427-439.

酿酒酵母基因组进化的研究进展

Advances in genome evolution of Saccharomyces cerevisiae

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 63

相关文章 14

编辑推荐

Metrics

本文评价