利用计算代谢组学策略研究植物特异性代谢物。
Studying Plant Specialized Metabolites Using Computational Metabolomics Strategies.
机构信息
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czechia.
Department of Genetics and Microbiology, Faculty of Science, Charles University, Prague, Czechia.
出版信息
Methods Mol Biol. 2024;2788:97-136. doi: 10.1007/978-1-0716-3782-1_7.
Plant specialized metabolites have diversified vastly over the course of plant evolution, and they are considered key players in complex interactions between plants and their environment. The chemical diversity of these metabolites has been widely explored and utilized in agriculture and crop enhancement, the food industry, and drug development, among other areas. However, the immensity of the plant metabolome can make its exploration challenging. Here we describe a protocol for exploring plant specialized metabolites that combines high-resolution mass spectrometry and computational metabolomics strategies, including molecular networking, identification of structural motifs, as well as prediction of chemical structures and metabolite classes.
植物次生代谢物在植物进化过程中发生了多样化,它们被认为是植物与其环境之间复杂相互作用的关键参与者。这些代谢物的化学多样性在农业和作物改良、食品工业和药物开发等领域得到了广泛的探索和利用。然而,植物代谢组的巨大规模使得其探索具有挑战性。在这里,我们描述了一种结合高分辨率质谱和计算代谢组学策略的植物次生代谢物研究方案,包括分子网络、结构基序的鉴定以及化学结构和代谢物类别的预测。