Plant Biology Division, The Samuel Roberts Noble Foundation , 2510 Sam Noble Parkway, Ardmore, Oklahoma 73401, United States.
Department of Biochemistry, University of Missouri , Bond Life Sciences Center, 1201 Rollins Street, Columbia, Missouri 65211, United States.
Anal Chem. 2016 Dec 6;88(23):11373-11383. doi: 10.1021/acs.analchem.6b00906. Epub 2016 Nov 23.
Custom software entitled Plant Metabolite Annotation Toolbox (PlantMAT) has been developed to address the number one grand challenge in metabolomics, which is the large-scale and confident identification of metabolites. PlantMAT uses informed phytochemical knowledge for the prediction of plant natural products such as saponins and glycosylated flavonoids through combinatorial enumeration of aglycone, glycosyl, and acyl subunits. Many of the predicted structures have yet to be characterized and are absent from traditional chemical databases, but have a higher probability of being present in planta. PlantMAT allows users to operate an automated and streamlined workflow for metabolite annotation from a user-friendly interface within Microsoft Excel, a familiar, easily accessed program for chemists and biologists. The usefulness of PlantMAT is exemplified using ultrahigh-performance liquid chromatography-electrospray ionization quadrupole time-of-flight tandem mass spectrometry (UHPLC-ESI-QTOF-MS/MS) metabolite profiling data of saponins and glycosylated flavonoids from the model legume Medicago truncatula. The results demonstrate PlantMAT substantially increases the chemical/metabolic space of traditional chemical databases. Ten of the PlantMAT-predicted identifications were validated and confirmed through the isolation of the compounds using ultrahigh-performance liquid chromatography-mass spectrometry-solid-phase extraction (UHPLC-MS-SPE) followed by de novo structural elucidation using 1D/2D nuclear magnetic resonance (NMR). It is further demonstrated that PlantMAT enables the dereplication of previously identified metabolites and is also a powerful tool for the discovery of structurally novel metabolites.
自定义软件题为植物代谢物注释工具箱（PlantMAT）已经开发，以解决代谢组学的头号重大挑战，这是大规模和有信心的代谢物鉴定。PlantMAT 通过糖苷、糖基和酰基亚基的组合枚举，利用有关植物化学物质的知识来预测植物天然产物，如皂苷和糖基化类黄酮。许多预测的结构尚未被表征，并且不存在于传统的化学数据库中，但在植物中更有可能存在。PlantMAT 允许用户在 Microsoft Excel 中的用户友好界面中操作自动化和简化的代谢物注释工作流程，这是化学家与生物学家熟悉且易于访问的程序。使用来自模式豆科植物百脉根的皂苷和糖基化类黄酮的超高效液相色谱 - 电喷雾电离四极杆飞行时间串联质谱（UHPLC-ESI-QTOF-MS/MS）代谢物分析数据，说明了 PlantMAT 的实用性。结果表明，PlantMAT 大大增加了传统化学数据库的化学/代谢空间。通过使用超高效液相色谱 - 质谱 - 固相萃取（UHPLC-MS-SPE）分离化合物，然后使用一维/二维核磁共振（NMR）进行从头结构阐明，验证并确认了 PlantMAT 预测的 10 种鉴定结果。进一步表明，PlantMAT 可以使先前鉴定的代谢物去重复，并且也是发现结构新颖代谢物的有力工具。
