TY - JOUR
T1 - Advanced genome-editing technologies enable rapid and large-scale generation of genetic variants for strain engineering and synthetic biology
AU - Zeng, Yi
AU - Hong, Yuxiang
AU - Azi, Fidelis
AU - Liu, Yugeng
AU - Chen, Yousheng
AU - Guo, Chuchu
AU - Lin, Dewei
AU - Wu, Zizhao
AU - Chen, Wenhao
AU - Xu, Peng
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Targeted genome editing not only improves our understanding of fundamental rules in life sciences but also affords us versatile toolkits to improve industrially relevant phenotypes in various host cells. In this review, we summarize the recent endeavor to develop efficient genome-editing tools, and emphasize the utility of these tools to generate massive scale of genetic variants. We categorize these tools into traditional recombination-based tools, and more advanced CRISPR as well as RNA-based genome-editing tools. This diverse panel of sophisticated tools has been applied to accelerate strain engineering, upgrade biomanufacturing, and customize biosensing. In parallel with high-throughput phenotyping and AI-based optimization algorithms, we envision that genome-editing technologies will become a driving force to automate and streamline biological engineering, and empower us to address critical challenges in health, environment, energy, and sustainability.
AB - Targeted genome editing not only improves our understanding of fundamental rules in life sciences but also affords us versatile toolkits to improve industrially relevant phenotypes in various host cells. In this review, we summarize the recent endeavor to develop efficient genome-editing tools, and emphasize the utility of these tools to generate massive scale of genetic variants. We categorize these tools into traditional recombination-based tools, and more advanced CRISPR as well as RNA-based genome-editing tools. This diverse panel of sophisticated tools has been applied to accelerate strain engineering, upgrade biomanufacturing, and customize biosensing. In parallel with high-throughput phenotyping and AI-based optimization algorithms, we envision that genome-editing technologies will become a driving force to automate and streamline biological engineering, and empower us to address critical challenges in health, environment, energy, and sustainability.
U2 - 10.1016/j.mib.2022.102175
DO - 10.1016/j.mib.2022.102175
M3 - 文章
C2 - 35809388
SN - 1369-5274
VL - 69
JO - Current Opinion in Microbiology
JF - Current Opinion in Microbiology
ER -