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将串联质谱文库扩展到包括在源内产生的碎片离子的 MS 谱和 MS 谱。

Extending a Tandem Mass Spectral Library to Include MS Spectra of Fragment Ions Produced In-Source and MS Spectra.

机构信息

Mass Spectrometry Data Center, National Institute of Standards and Technology, Mail Stop 8362, Gaithersburg, MD, 20899, USA.

出版信息

J Am Soc Mass Spectrom. 2017 Nov;28(11):2280-2287. doi: 10.1007/s13361-017-1748-2. Epub 2017 Jul 18.

Abstract

Tandem mass spectral library searching is finding increased use as an effective means of determining chemical identity in mass spectrometry-based omics studies. We previously reported on constructing a tandem mass spectral library that includes spectra for multiple precursor ions for each analyte. Here we report our method for expanding this library to include MS spectra of fragment ions generated during the ionization process (in-source fragment ions) as well as MS and MS spectra. These can assist the chemical identification process. A simple density-based clustering algorithm was used to cluster all significant precursor ions from MS scans for an analyte acquired during an infusion experiment. The MS spectra associated with these precursor ions were grouped into the same precursor clusters. Subsequently, a new top-down hierarchical divisive clustering algorithm was developed for clustering the spectra from fragmentation of ions in each precursor cluster, including the MS spectra of the original precursors and of the in-source fragments as well as the MS spectra. This algorithm starts with all the spectra of one precursor in one cluster and then separates them into sub-clusters of similar spectra based on the fragment patterns. Herein, we describe the algorithms and spectral evaluation methods for extending the library. The new library features were demonstrated by searching the high resolution spectra of E. coli extracts against the extended library, allowing identification of compounds and their in-source fragment ions in a manner that was not possible before. Graphical Abstract ᅟ.

摘要

串联质谱文库检索作为一种有效的确定基于质谱组学研究中化学物质身份的方法,其使用正在不断增加。我们之前曾报道过构建串联质谱文库的方法,其中包括每个分析物的多个前体离子的光谱。在这里,我们报告了扩展该文库的方法,包括在电离过程中产生的碎片离子(源内碎片离子)以及 MS 和 MS/MS 光谱的 MS 光谱。这些可以辅助化学鉴定过程。使用基于密度的聚类算法对在注入实验中获得的分析物的 MS 扫描中所有重要的前体离子进行聚类。与这些前体离子相关的 MS 光谱被分组到相同的前体簇中。随后,开发了一种新的自上而下的分层分裂聚类算法,用于对每个前体簇中离子碎裂产生的光谱进行聚类,包括原始前体和源内碎片的 MS 光谱以及 MS/MS 光谱。该算法从一个簇中的所有一个前体的光谱开始,然后根据碎片模式将它们分成相似光谱的子簇。在此,我们描述了扩展库的算法和光谱评估方法。通过将大肠杆菌提取物的高分辨率光谱与扩展库进行搜索,展示了新库的功能,以以前不可能的方式鉴定化合物及其源内碎片离子。

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