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Programming cells by multiplex genome engineering and accelerated evolution

基因组工程 基因组 计算生物学 代谢工程 背景(考古学) 生物 合成生物学 定向进化 多路复用 遗传学 基因 基因组编辑 突变体 古生物学
作者
Harris H. Wang,Farren J. Isaacs,Peter A. Carr,Zachary Z. Sun,George Xu,Craig R. Forest,George M. Church
出处
期刊:Nature [Springer Nature]
卷期号:460 (7257): 894-898 被引量:1449
标识
DOI:10.1038/nature08187
摘要

Genomic diversity is difficult to generate in the laboratory in an efficient way. A new technique called MAGE (multiplex automated genome engineering), described here, simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thereby producing combinatorial genomic diversity. This is an automated and efficient approach that expedites the design and evolution of organisms with new and improved properties. Genomic diversity is difficult to generate in the laboratory in an efficient way. Here, multiplex automated genome engineering (MAGE) is described for large-scale programming and evolution of cells. It is an automated and efficient approach that expedites the design and evolution of organisms with new and improved properties. The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments1,2. However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales3. Although in vitro and directed evolution methods4,5,6,7,8,9 have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes. Here, we describe multiplex automated genome engineering (MAGE) for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes (mismatches, insertions, deletions). We applied MAGE to optimize the 1-deoxy-d-xylulose-5-phosphate (DXP) biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4.3 billion combinatorial genomic variants per day. We isolated variants with more than fivefold increase in lycopene production within 3 days, a significant improvement over existing metabolic engineering techniques. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.
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