Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), 85354 Freising, Germany.
Institute of Plant Genetics, Leibniz University Hannover, 30167 Hannover, Germany.
Nutrients. 2023 Feb 3;15(3):783. doi: 10.3390/nu15030783.
Plants are an indispensable cornerstone of sustainable global food supply. While immense progress has been made in decoding the genomes of crops in recent decades, the composition of their proteomes, the entirety of all expressed proteins of a species, is virtually unknown. In contrast to the model plant , proteomic analyses of crop plants have often been hindered by the presence of extreme concentrations of secondary metabolites such as pigments, phenolic compounds, lipids, carbohydrates or terpenes. As a consequence, crop proteomic experiments have, thus far, required individually optimized protein extraction protocols to obtain samples of acceptable quality for downstream analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). In this article, we present a universal protein extraction protocol originally developed for gel-based experiments and combined it with an automated single-pot solid-phase-enhanced sample preparation (SP3) protocol on a liquid handling robot to prepare high-quality samples for proteomic analysis of crop plants. We also report an automated offline peptide separation protocol and optimized micro-LC-MS/MS conditions that enables the identification and quantification of ~10,000 proteins from plant tissue within 6 h of instrument time. We illustrate the utility of the workflow by analyzing the proteomes of mature tomato fruits to an unprecedented depth. The data demonstrate the robustness of the approach which we propose for use in upcoming large-scale projects that aim to map crop tissue proteomes.
植物是可持续全球粮食供应不可或缺的基石。尽管近几十年来在解码作物基因组方面取得了巨大进展,但它们的蛋白质组组成,即物种所有表达蛋白的总和,实际上还未知。与模式植物相比,作物的蛋白质组分析常常受到大量存在的次级代谢产物的阻碍,如色素、酚类化合物、脂质、碳水化合物或萜类化合物。因此,迄今为止,作物蛋白质组实验需要单独优化蛋白质提取方案,以获得可接受质量的样品,用于通过液相色谱串联质谱 (LC-MS/MS) 进行下游分析。在本文中,我们提出了一种通用的蛋白质提取方案,最初是为凝胶实验开发的,并将其与在液体处理机器人上自动进行的单孔固相增强样品制备 (SP3) 方案相结合,以制备高质量的作物蛋白质组分析样品。我们还报告了一种自动化的离线肽分离方案和优化的微 LC-MS/MS 条件,使我们能够在 6 小时的仪器时间内从植物组织中鉴定和定量约 10,000 种蛋白质。我们通过分析成熟番茄果实的蛋白质组来证明该工作流程的实用性,达到了前所未有的深度。该数据证明了该方法的稳健性,我们建议将其用于即将进行的旨在绘制作物组织蛋白质组图谱的大规模项目中。