Transcriptome based functional identification and application of regulator AbrB on alkaline protease synthesis in Bacillus licheniformis 2709

地衣芽孢杆菌 蛋白酶 生物 基因 抑制因子 转录因子 转录组 生物化学 基因表达 化学 遗传学 枯草芽孢杆菌 细菌
作者
Cuixia Zhou,Huitu Zhang,Honglei Fang,Yanqing Sun,Huiying Zhou,Guangcheng Yang,Lu Fuping
出处
期刊:International Journal of Biological Macromolecules [Elsevier]
卷期号:166: 1491-1498 被引量:11
标识
DOI:10.1016/j.ijbiomac.2020.11.028
摘要

Bacillus licheniformis 2709 is the major alkaline protease producer, which has great potential value of industrial application, but how the high-producer can be regulated rationally is still not completely understood. It's meaningful to understand the metabolic processes during alkaline protease production in industrial fermentation medium. Here, we collected the transcription database at various enzyme-producing stages (preliminary stage, stable phase and decline phase) to specifically research the synthesized and regulatory mechanism of alkaline protease in B. licheniformis. The RNA-sequencing analysis showed differential expression of numerous genes related to several processes, among which genes correlated with regulators were concerned, especially the major differential gene abrB on enzyme (AprE) synthesis was investigated. It was further verified that AbrB is a repressor of AprE by plasmid-mediated over-expression due to the severely descending enzyme activity (11,300 U/mL to 2695 U/mL), but interestingly it is indispensable for alkaline protease production because the enzyme activity of the null abrB mutant was just about 2279 U/mL. Thus, we investigated the aprE transcription by eliminating the theoretical binding site (TGGAA) of AbrB protein predicated by computational strategy, which significantly improved the enzyme activity by 1.21-fold and gene transcription level by 1.77-fold in the mid-log phase at a cultivation time of 18 h. Taken together, it is of great significance to improve the production strategy, control the metabolic process and oriented engineering by rational molecular modification of regulatory network based on the high throughput sequencing and computational prediction.
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