MS-DIAL：用于全面代谢组分析的非数据依赖型串联质谱去卷积方法
MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis.
作者信息
Tsugawa Hiroshi, Cajka Tomas, Kind Tobias, Ma Yan, Higgins Brendan, Ikeda Kazutaka, Kanazawa Mitsuhiro, VanderGheynst Jean, Fiehn Oliver, Arita Masanori
机构信息
1] RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa, Japan. [2] Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka, Japan.
Genome Center, University of California Davis, Davis, California, USA.
出版信息
Nat Methods. 2015 Jun;12(6):523-6. doi: 10.1038/nmeth.3393. Epub 2015 May 4.
Data-independent acquisition (DIA) in liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) provides comprehensive untargeted acquisition of molecular data. We provide an open-source software pipeline, which we call MS-DIAL, for DIA-based identification and quantification of small molecules by mass spectral deconvolution. For a reversed-phase LC-MS/MS analysis of nine algal strains, MS-DIAL using an enriched LipidBlast library identified 1,023 lipid compounds, highlighting the chemotaxonomic relationships between the algal strains.
液相色谱（LC）与串联质谱（MS/MS）联用中的数据非依赖型采集（DIA）可提供对分子数据的全面非靶向采集。我们提供了一个开源软件流程，称为MS-DIAL，用于通过质谱去卷积对小分子进行基于DIA的鉴定和定量。对于9种藻类菌株的反相LC-MS/MS分析，使用富集的LipidBlast库的MS-DIAL鉴定出1023种脂质化合物，突出了藻类菌株之间的化学分类关系。
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