National Centre for Plant Gene Research (Beijing), Innovation Academy for Seed Design, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, P. R. China.
University of Chinese Academy of Sciences, Beijing 100039, P. R. China.
Plant Commun. 2020 Apr 21;1(3):100047. doi: 10.1016/j.xplc.2020.100047. eCollection 2020 May 11.
One of the hottest topics in plant hormone biology is the crosstalk mechanisms, whereby multiple classes of phytohormones interplay with each other through signaling networks. To better understand the roles of hormonal crosstalks in their complex regulatory networks, it is of high significance to investigate the spatial and temporal distributions of multiple -phytohormones simultaneously from one plant tissue sample. In this study, we develop a high-sensitivity and high-throughput method for the simultaneous quantitative analysis of 44 phytohormone compounds, covering currently known 10 major classes of phytohormones (strigolactones, brassinosteroids, gibberellins, auxin, abscisic acid, jasmonic acid, salicylic acid, cytokinins, ethylene, and polypeptide hormones [e.g., phytosulfokine]) from only 100 mg of plant sample. These compounds were grouped and purified separately with a tailored solid-phase extraction procedure based on their physicochemical properties and then analyzed by LC-MS/MS. The recoveries of our method ranged from 49.6% to 99.9% and the matrix effects from 61.8% to 102.5%, indicating that the overall sample pretreatment design resulted in good purification. The limits of quantitation (LOQs) of our method ranged from 0.06 to 1.29 pg/100 mg fresh weight and its precision was less than 13.4%, indicating high sensitivity and good reproducibility of the method. Tests of our method in different plant matrices demonstrated its wide applicability. Collectively, these advantages will make our method helpful in clarifying the crosstalk networks of phytohormones.
植物激素生物学中最热门的话题之一是串扰机制,通过信号网络,多种植物激素相互作用。为了更好地理解激素串扰在其复杂调控网络中的作用,同时从一个植物组织样本中同时研究多种植物激素的时空分布具有重要意义。在本研究中,我们开发了一种高灵敏度和高通量的方法,用于同时定量分析 44 种植物激素化合物,涵盖目前已知的 10 大类植物激素(独脚金内酯、油菜素内酯、赤霉素、生长素、脱落酸、茉莉酸、水杨酸、细胞分裂素、乙烯和多肽激素[如植物磺基肽]) 仅从 100 毫克植物样本中。这些化合物根据其物理化学性质分别进行分组和纯化,然后通过 LC-MS/MS 进行分析。我们方法的回收率范围为 49.6%至 99.9%,基质效应范围为 61.8%至 102.5%,表明总体样品预处理设计导致了良好的纯化效果。我们方法的定量下限(LOQ)范围为 0.06 至 1.29 pg/100 毫克鲜重,其精密度小于 13.4%,表明该方法具有高灵敏度和良好的重现性。在不同植物基质中的方法测试表明其具有广泛的适用性。总的来说,这些优势将使我们的方法有助于阐明植物激素的串扰网络。