代谢组学研究对于理解植物代谢如何响应环境条件的变化变得越来越普遍。遗传操作,和治疗。尽管代谢组学工作流程最近取得了进展,样品制备过程仍然限制了大规模研究中的高通量分析。这里,我们提出了一个高度灵活的机器人系统,集成了液体处理,超声处理,离心,溶剂蒸发,并在96孔板中处理样品转移,以自动从叶片样品中提取代谢物。我们将既定的手动提取协议转移到机器人系统,有了这个,我们展示了优化步骤,以提高重现性,并在提取效率和准确性方面获得可比的结果。然后,我们测试了机器人系统,以在无应力条件下分析野生型和四个转基因白桦树(Betulapendula)品系的代谢组。对桦树进行了工程改造,以过度表达杨树(Populusxcanescens)异戊二烯合酶(PcISPS)并释放各种量的异戊二烯。通过将转基因树的不同异戊二烯排放能力与其叶代谢组拟合,我们观察到一些类黄酮和其他次生代谢产物以及碳水化合物的异戊二烯依赖性上调,氨基酸和脂质代谢产物。相比之下,发现二糖蔗糖与异戊二烯排放呈强烈负相关。提出的研究说明了集成机器人技术以增加样品吞吐量的力量,减少人为错误和劳动时间,并确保完全控制,监控,和标准化的样品制备程序。由于其模块化和灵活的结构,机器人系统可以很容易地适应其他提取协议,用于分析各种组织或植物物种,以实现植物研究中的高通量代谢组学。
Metabolomics studies are becoming increasingly common for understanding how plant metabolism responds to changes in environmental conditions, genetic manipulations and treatments. Despite the recent advances in metabolomics workflow, the sample preparation process still limits the high-throughput analysis in large-scale studies. Here, we present a highly flexible robotic system that integrates liquid handling, sonication, centrifugation, solvent evaporation and sample transfer processed in 96-well plates to automatize the metabolite extraction from leaf samples. We transferred an established manual extraction protocol performed to a robotic system, and with this, we show the optimization steps required to improve reproducibility and obtain comparable results in terms of extraction efficiency and accuracy. We then tested the robotic system to analyze the metabolomes of wild-type and four transgenic silver birch (Betula pendula Roth) lines under unstressed conditions. Birch trees were engineered to overexpress the poplar (Populus × canescens) isoprene synthase and to emit various amounts of isoprene. By fitting the different isoprene emission capacities of the transgenic trees with their leaf metabolomes, we observed an isoprene-dependent upregulation of some flavonoids and other secondary metabolites as well as carbohydrates, amino acid and lipid metabolites. By contrast, the disaccharide sucrose was found to be strongly negatively correlated to isoprene emission. The presented study illustrates the power of integrating robotics to increase the sample throughput, reduce human errors and labor time, and to ensure a fully controlled, monitored and standardized sample preparation procedure. Due to its modular and flexible structure, the robotic system can be easily adapted to other extraction protocols for the analysis of various tissues or plant species to achieve high-throughput metabolomics in plant research.