Neumann Nora K N, Lehner Sylvia M, Kluger Bernhard, Bueschl Christoph, Sedelmaier Karoline, Lemmens Marc, Krska Rudolf, Schuhmacher Rainer
Center for Analytical Chemistry, ‡Institute for Biotechnology in Plant Production, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna (BOKU) , Konrad Lorenz Strasse 20, 3430 Tulln, Austria.
Anal Chem. 2014 Aug 5;86(15):7320-7. doi: 10.1021/ac501358z. Epub 2014 Jul 14.
Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native (12)C- and uniformly (13)C (U-(13)C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-(13)C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research.
生物化合物的结构解析仍然是代谢组学研究中非靶向液相色谱-高分辨质谱（LC-HRMS）方法的主要瓶颈。本研究的目的是将稳定同位素标记与串联质谱相结合，用于自动解释碎片离子的元素组成，从而促进代谢物的结构表征。开发了软件工具FragExtract，并分别用10种真菌物质的天然（12）C和均匀（13）C（U-（13）C）标记的分析标准品在纯溶剂中以及加标到禾谷镰刀菌的真菌培养滤液中的LC-HRMS/MS光谱进行了评估。此外，以非靶向代谢组学实验得到的禾谷镰刀菌样品中包含的9种未知生化化合物为例说明了所开发的方法。天然和U-（13）C标记化合物的MS/MS光谱中相应碎片离子之间的质量差异使得能够为每个碎片信号确定碳原子数，并允许为每个碎片离子生成有意义的假定分子式，这反过来也有助于确定前体离子的元素组成。与费力的MS/MS光谱手动分析相比，所提出的算法标志着未来非靶向代谢组学研究中朝着高效的碎片信号解析和代谢物结构注释迈出的重要一步。此外，如对真菌培养样品所示，FragExtract还有助于表征数据库中未包含的未知代谢物，因此对非靶向代谢组学研究有重大贡献。
