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从层次串联质谱数据中自动分配脂质 A 结构。

Automated lipid A structure assignment from hierarchical tandem mass spectrometry data.

机构信息

Department of Medicinal Chemistry, University of Washington, Box 357610, Seattle, WA 98195-7610, USA.

出版信息

J Am Soc Mass Spectrom. 2011 May;22(5):856-66. doi: 10.1007/s13361-010-0055-y. Epub 2011 Mar 5.

DOI:10.1007/s13361-010-0055-y
PMID:21472520
Abstract

Infusion-based electrospray ionization (ESI) coupled to multiple-stage tandem mass spectrometry (MS(n)) is a standard methodology for investigating lipid A structural diversity (Shaffer et al. J. Am. Soc. Mass. Spectrom. 18(6), 1080-1092, 2007). Annotation of these MS(n) spectra, however, has remained a manual, expert-driven process. In order to keep up with the data acquisition rates of modern instruments, we devised a computational method to annotate lipid A MS(n) spectra rapidly and automatically, which we refer to as hierarchical tandem mass spectrometry (HiTMS) algorithm. As a first-pass tool, HiTMS aids expert interpretation of lipid A MS(n ) data by providing the analyst with a set of candidate structures that may then be confirmed or rejected. HiTMS deciphers the signature ions (e.g., A-, Y-, and Z-type ions) and neutral losses of MS(n) spectra using a species-specific library based on general prior structural knowledge of the given lipid A species under investigation. Candidates are selected by calculating the correlation between theoretical and acquired MS(n) spectra. At a false discovery rate of less than 0.01, HiTMS correctly assigned 85% of the structures in a library of 133 manually annotated Francisella tularensis subspecies novicida lipid A structures. Additionally, HiTMS correctly assigned 85% of the structures in a smaller library of lipid A species from Yersinia pestis demonstrating that it may be used across species.

摘要

基于输液的电喷雾电离 (ESI) 与多级串联质谱 (MS(n)) 相结合,是研究脂质 A 结构多样性的标准方法(Shaffer 等人,J. Am. Soc. Mass. Spectrom. 18(6), 1080-1092, 2007)。然而,这些 MS(n) 谱的注释仍然是一个手动的、专家驱动的过程。为了跟上现代仪器的数据采集速度,我们设计了一种计算方法,可以快速自动注释脂质 A MS(n) 谱,我们称之为分层串联质谱 (HiTMS) 算法。作为第一个工具,HiTMS 通过为分析师提供一组可能被确认或拒绝的候选结构,来帮助专家解释脂质 A MS(n) 数据。HiTMS 使用基于给定脂质 A 物种的一般先前结构知识的特定物种库,通过解析特征离子(例如,A-、Y-和 Z-型离子)和 MS(n) 谱的中性损失,来破译 MS(n) 谱。通过计算理论和获得的 MS(n) 谱之间的相关性来选择候选物。在假发现率低于 0.01 的情况下,HiTMS 正确分配了 133 个手动注释的弗朗西斯氏菌亚种 novicida 脂质 A 结构库中 85%的结构。此外,HiTMS 正确分配了 85%来自鼠疫耶尔森氏菌的脂质 A 物种库中的结构,表明它可以在不同物种中使用。

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