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蛋白质组学和代谢组学在微生物代谢工程中的应用
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  • 英文篇名:Application of proteomics and metabolomics in microbial metabolic engineering
  • 作者:禹伟 ; 高教琪 ; 周雍进
  • 英文作者:YU Wei;GAO Jiaoqi;ZHOU Yongjin;CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences;
  • 关键词:蛋白质组学 ; 代谢组学 ; 基因组尺度代谢模型 ; 植物次级代谢 ; 微生物代谢工程 ; 综述
  • 英文关键词:proteomics;;metabolomics;;genome-scale metabolic model;;plant secondary metabolism;;microbial metabolic engineering;;review
  • 中文刊名:SPZZ
  • 英文刊名:Chinese Journal of Chromatography
  • 机构:中国科学院大连化学物理研究所中国科学院分离分析化学重点实验室;
  • 出版日期:2019-08-08
  • 出版单位:色谱
  • 年:2019
  • 期:v.37
  • 基金:国家自然科学基金面上项目(21877111,21808216);; 中国科学院大连化学物理研究所DMTO创新基金(DICP DMTO201701)~~
  • 语种:中文;
  • 页:SPZZ201908003
  • 页数:8
  • CN:08
  • ISSN:21-1185/O6
  • 分类号:24-31
摘要
构建微生物细胞工厂是化学品、生物能源以及药物分子可持续生产的可行性策略。然而,微生物的代谢复杂、调控严谨,制约着目标产物高效合成。蛋白质组学和代谢组学可以从系统生物学角度分析酶和代谢物组分,从而理解复杂的生物系统,为微生物代谢工程改造提供重要线索。该文介绍了蛋白质组学和代谢组学在微生物代谢工程中的应用,包括基因组尺度代谢模型构建、菌株生物合成优化、指导菌株耐受性改造、限速步骤预测、植物次级代谢途径挖掘,从而为微生物合成天然产物提供新的基因或途径。在此基础上,该文还展望了生物大数据未来的发展方向。
        Construction of microbial cell factories is a feasible strategy for the sustainable production of chemicals, biofuels, and pharmaceutical molecules. However, the complex metabolism and rigid regulation of microbes hinders the efficient synthesis of the products of interest. Proteomics and metabolomics analyze enzymes and metabolites in terms of systems biology, thus unraveling complex biological systems and providing significant clues for microbial metabolic engineering. Here, the applications of proteomics and metabolomics in microbial metabolic engineering were reviewed, including the construction of genome-scale metabolic models, optimization of microbial product synthesis, guidance of microbial stress tolerance engineering, and prediction of rate-limiting steps. In addition, proteomics and metabolomics could be employed to explore secondary metabolic pathways in plants, to reveal novel genes or pathways for microbial synthesis of natural products. Finally, the development of bio-big data was discussed.
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