清脆的
计算生物学
类型(生物学)
干扰(通信)
生物
CRISPR干扰
计算机科学
遗传学
基因组编辑
电信
基因
生态学
频道(广播)
作者
Katia Tarasava,Rongming Liu,Andrew D. Garst,Ryan T. Gill
摘要
Optimization of metabolic flux is a difficult and time-consuming process that often involves changing the expression levels of multiple genes simultaneously. While some pathways have a known rate limiting step, more complex metabolic networks can require a trial-and-error approach of tuning the expression of multiple genes to achieve a desired distribution of metabolic resources. Here we present an efficient method for generating expression diversity on a combinatorial scale using CRISPR interference. We use a modified native Escherichia coli Type I-E CRISPR-Cas system and an iterative cloning strategy for construction of guide RNA arrays. This approach allowed us to build a combinatorial gene expression library three orders of magnitude larger than previous studies. In less than 1 month, we generated ∼12,000 combinatorial gene expression variants that target six different genes and screened these variants for increased malonyl-CoA flux and 3-hydroxypropionate (3HP) production. We were able to identify a set of variants that exhibited a significant increase in malonyl-CoA flux and up to a 98% increase in 3HP production. This approach provides a fast and easy-to-implement strategy for engineering metabolic pathway flux for development of industrially relevant strains, as well as investigation of fundamental biological questions.
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