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MicroTom 代谢网络:在整个生长周期中重塑番茄代谢调控网络。

MicroTom Metabolic Network: Rewiring Tomato Metabolic Regulatory Network throughout the Growth Cycle.

机构信息

Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, Sichuan, People's Republic of China.

Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany; Center of Plant Systems Biology and Plant Biotechnology, 4000 Plovdiv, Bulgaria.

出版信息

Mol Plant. 2020 Aug 3;13(8):1203-1218. doi: 10.1016/j.molp.2020.06.005. Epub 2020 Jun 16.

DOI:10.1016/j.molp.2020.06.005
PMID:32561360
Abstract

Tomato (Solanum lycopersicum) is a major horticultural crop worldwide and has emerged as a preeminent model for metabolic research. Although many research efforts have focused on the analysis of metabolite differences between varieties and species, the dynamics of metabolic changes during the tomato growth cycle and the regulatory networks that underlie these changes are poorly understood. In this study, we integrated high-resolution spatio-temporal metabolome and transcriptome data to systematically explore the metabolic landscape across 20 major tomato tissues and growth stages. In the resulting MicroTom Metabolic Network, the 540 detected metabolites and their co-expressed genes could be divided into 10 distinct clusters based on their biological functions. Using this dataset, we constructed a global map of the major metabolic changes that occur throughout the tomato growth cycle and dissected the underlying regulatory network. In addition to verifying previously well-established regulatory networks for important metabolites, we identified novel transcription factors that regulate the biosynthesis of important secondary metabolites such as steroidal glycoalkaloids and flavonoids. Our findings provide insights into spatio-temporal changes in tomato metabolism and generate a valuable resource for the study of metabolic regulatory processes in model plants.

摘要

番茄(Solanum lycopersicum)是全球重要的园艺作物,已成为代谢研究的卓越模式生物。尽管许多研究都集中在分析品种和物种之间的代谢物差异上,但番茄生长周期中代谢变化的动态及其变化背后的调控网络仍知之甚少。在这项研究中,我们整合了高分辨率的时空代谢组学和转录组学数据,系统地研究了 20 种主要番茄组织和生长阶段的代谢景观。在生成的 MicroTom 代谢网络中,根据其生物学功能,可将 540 种检测到的代谢物及其共表达基因分为 10 个不同的簇。利用该数据集,我们构建了番茄整个生长周期中主要代谢变化的全局图谱,并剖析了其背后的调控网络。除了验证先前已确立的重要代谢物的调控网络外,我们还鉴定了调控重要次生代谢物(如甾体糖苷生物碱和类黄酮)生物合成的新转录因子。我们的研究结果提供了对番茄代谢时空变化的深入了解,并为研究模式植物的代谢调控过程生成了有价值的资源。

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