联合囊肿
代谢组学
丁醇
生物
代谢工程
计算生物学
基因
蓝藻
转录组
光合作用
生物化学
遗传学
突变体
细菌
生物信息学
基因表达
乙醇
作者
Hongji Zhu,Xiaoyue Ren,Jiangxin Wang,Zhongdi Song,Mengliang Shi,Jianjun Qiao,Xiaoxu Tian,Jie Liu,Lei Chen,Weiwen Zhang
标识
DOI:10.1186/1754-6834-6-106
摘要
Abstract Background Photosynthetic cyanobacteria have been recently proposed as a ‘microbial factory’ to produce butanol due to their capability to utilize solar energy and CO 2 as the sole energy and carbon sources, respectively. However, to improve the productivity, one key issue needed to be addressed is the low tolerance of the photosynthetic hosts to butanol. Results In this study, we first applied a quantitative transcriptomics approach with a next-generation RNA sequencing technology to identify gene targets relevant to butanol tolerance in a model cyanobacterium Synechocystis sp. PCC 6803. The results showed that 278 genes were induced by the butanol exposure at all three sampling points through the growth time course. Genes encoding heat-shock proteins, oxidative stress related proteins, transporters and proteins involved in common stress responses, were induced by butanol exposure. We then applied GC-MS based metabolomics analysis to determine the metabolic changes associated with the butanol exposure. The results showed that 46 out of 73 chemically classified metabolites were differentially regulated by butanol treatment. Notably, 3-phosphoglycerate, glycine, serine and urea related to general stress responses were elevated in butanol-treated cells. To validate the potential targets, we constructed gene knockout mutants for three selected gene targets. The comparative phenotypic analysis confirmed that these genes were involved in the butanol tolerance. Conclusion The integrated OMICS analysis provided a comprehensive view of the complicated molecular mechanisms employed by Synechocystis sp. PCC 6803 against butanol stress, and allowed identification of a series of potential gene candidates for tolerance engineering in cyanobacterium Synechocystis sp. PCC 6803.
科研通智能强力驱动
Strongly Powered by AbleSci AI