基因敲除
基因
RNA干扰
生物
计算生物学
重编程
遗传学
核糖核酸
作者
Chunlin Tan,Ping Xu,Fei Tao
出处
期刊:Research
[American Association for the Advancement of Science]
日期:2022-01-01
卷期号:2022
被引量:2
标识
DOI:10.34133/research.0017
摘要
Rationally controlling cellular metabolism is of great importance but challenging owing to its highly complex and chaotic nature. Natural existing sensory proteins like histidine kinases (HKs) are understood as “sensitive nodes” of biological networks that can trigger disruptive metabolic reprogramming (MRP) upon perceiving environmental fluctuation. Here, the “sensitive node” genes were adopted to devise a global MRP platform consisting of a CRISPR interference-mediated dual-gene combinational knockdown toolbox and survivorship-based metabolic interaction decoding algorithm. The platform allows users to decode the interfering effects of n × n gene pairs while only requiring the synthesis of n pairs of primers. A total of 35 HK genes and 24 glycine metabolic genes were selected as the targets to determine the effectiveness of our platform in a Vibrio sp. FA2. The platform was applied to decode the interfering impact of HKs on antibiotic resistance in strain FA2. A pattern of combined knockdown of HK genes ( sasA_8 and 04288 ) was demonstrated to be capable of reducing antibiotic resistance of Vibrio by 108-fold. Patterns of combined knockdown of glycine pathway genes (e.g., gcvT and ltaE ) and several HK genes (e.g., cpxA and btsS ) were also revealed to increase glycine production. Our platform may enable an efficient and rational approach for global MRP based on the elucidation of high-order gene interactions. A web-based 1-stop service ( https://smrp.sjtu.edu.cn ) is also provided to simplify the implementation of this smart strategy in a broad range of cells.
科研通智能强力驱动
Strongly Powered by AbleSci AI