Doppler Maria, Kluger Bernhard, Bueschl Christoph, Schneider Christina, Krska Rudolf, Delcambre Sylvie, Hiller Karsten, Lemmens Marc, Schuhmacher Rainer
Center for Analytical Chemistry, Department of Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad-Lorenz-Strasse 20, 3430 Tulln, Austria.
Institute for Biotechnology in Plant Production, Department of Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad-Lorenz-Strasse 20, 3430 Tulln, Austria.
Int J Mol Sci. 2016 Jun 28;17(7):1017. doi: 10.3390/ijms17071017.
The evaluation of extraction protocols for untargeted metabolomics approaches is still difficult. We have applied a novel stable isotope-assisted workflow for untargeted LC-HRMS-based plant metabolomics , which allows for the first time every detected feature to be considered for method evaluation. The efficiency and complementarity of commonly used extraction solvents, namely 1 + 3 (v/v) mixtures of water and selected organic solvents (methanol, acetonitrile or methanol/acetonitrile 1 + 1 (v/v)), with and without the addition of 0.1% (v/v) formic acid were compared. Four different wheat organs were sampled, extracted and analysed by LC-HRMS. Data evaluation was performed with the in-house-developed MetExtract II software and R. With all tested solvents a total of 871 metabolites were extracted in ear, 785 in stem, 733 in leaf and 517 in root samples, respectively. Between 48% (stem) and 57% (ear) of the metabolites detected in a particular organ were found with all extraction mixtures, and 127 of 996 metabolites were consistently shared between all extraction agent/organ combinations. In aqueous methanol, acidification with formic acid led to pronounced pH dependency regarding the precision of metabolite abundance and the number of detectable metabolites, whereas extracts of acetonitrile-containing mixtures were less affected. Moreover, methanol and acetonitrile have been found to be complementary with respect to extraction efficiency. Interestingly, the beneficial properties of both solvents can be combined by the use of a water-methanol-acetonitrile mixture for global metabolite extraction instead of aqueous methanol or aqueous acetonitrile alone.
对非靶向代谢组学方法的提取方案进行评估仍然具有挑战性。我们将一种新型的稳定同位素辅助工作流程应用于基于非靶向液相色谱-高分辨质谱的植物代谢组学研究，首次能够对每个检测到的特征进行方法评估。比较了常用提取溶剂（即水与选定有机溶剂（甲醇、乙腈或甲醇/乙腈1 + 1（v/v））按1 + 3（v/v）混合）在添加和不添加0.1%（v/v）甲酸情况下的效率和互补性。采集了四种不同的小麦器官样本，通过液相色谱-高分辨质谱进行提取和分析。使用内部开发的MetExtract II软件和R进行数据评估。使用所有测试溶剂时，在穗部样本中分别提取了871种代谢物，茎部样本中提取了785种，叶片样本中提取了733种，根部样本中提取了517种。在特定器官中检测到的代谢物，有48%（茎部）至57%（穗部）可通过所有提取混合物找到，并且在所有提取剂/器官组合中，996种代谢物中有127种是共同存在的。在甲醇水溶液中，添加甲酸会导致代谢物丰度精度和可检测代谢物数量对pH有显著依赖性，而含乙腈混合物的提取物受影响较小。此外，发现甲醇和乙腈在提取效率方面具有互补性。有趣的是，通过使用水-甲醇-乙腈混合物进行整体代谢物提取，而不是单独使用甲醇水溶液或乙腈水溶液，可以将两种溶剂的有益特性结合起来。
