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基于多组学数据的植物三萜代谢多样性研究。

Multi-omics data-driven investigations of metabolic diversity of plant triterpenoids.

机构信息

The CAAS-YNNU-YINMORE Joint Academy of Potato Science, Yunnan Normal University, Kunming, 650500, China.

Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China.

出版信息

Plant J. 2019 Jan;97(1):101-111. doi: 10.1111/tpj.14132. Epub 2018 Dec 3.

Abstract

The vast majority of structurally diverse metabolites play essential roles in mediating the interactions between plant and environment, and constitute a valuable resource for industrial applications. Recent breakthroughs in sequencing technology have greatly accelerated metabolic studies of natural plant products, providing opportunities to investigate the molecular basis underlying the diversity of specialized plant metabolites through large-scale analysis. Here, we focus on the biosynthesis of plant triterpenoids, especially the three diversifying reactions (cyclization, oxidation and glycosylation) that largely contribute to the structural diversity of triterpenoids. Gene mining through large-scale omics data and functional characterization of metabolic genes including enzymes, transcription factors and transporters could provide important insights into the evolution of specialized plant metabolism and pave the way for the production of high-value metabolites or derivatives using synthetic biology approaches.

摘要

绝大多数结构多样的代谢物在介导植物与环境的相互作用方面发挥着重要作用,并且是工业应用的宝贵资源。近年来测序技术的突破极大地加速了天然植物产物的代谢研究,为通过大规模分析研究特化植物代谢物多样性的分子基础提供了机会。在这里,我们重点介绍植物三萜类化合物的生物合成,特别是对三萜类化合物结构多样性有重要贡献的三个多样化反应(环化、氧化和糖基化)。通过大规模组学数据的基因挖掘和代谢基因(包括酶、转录因子和转运蛋白)的功能表征,可以深入了解特化植物代谢的进化,并为使用合成生物学方法生产高价值代谢物或衍生物铺平道路。

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