Comprehensive Tandem-Mass-Spectrometry Coverage of Complex Samples Enabled by Data-Set-Dependent Acquisition

Tandem
mass spectrometry (MS/MS) is an invaluable experimental
tool for providing analytical data supporting the identification of
small molecules and peptides in mass-spectrometry-based “omics”
experiments. Data-dependent MS/MS (DDA) is a real-time MS/MS-acquisition
strategy that is responsive to the signals detected in a given sample.
However, in analysis of even moderately complex samples with state-of-the-art
instrumentation, the speed of MS/MS acquisition is insufficient to
offer comprehensive MS/MS coverage of all detected molecules. Data-independent
approaches (DIA) offer greater MS/MS coverage, typically at the expense
of selectivity or sensitivity. This report describes data-set-dependent
MS/MS (DsDA), a novel integration of MS1-data processing and target
prioritization to enable comprehensive MS/MS sampling during the initial
MS-level experiment. This approach is guided by the premise that in
omics experiments, individual injections are typically made as part
of a larger set of samples, and feedback between data processing and
data acquisition can allow approximately real-time optimization of
MS/MS-acquisition parameters and nearly complete MS/MS-sampling coverage.
Using a combination of R, Proteowizard, XCMS, and WRENS software,
this concept was implemented on a liquid-chromatograph-coupled quadrupole
time-of-flight mass spectrometer. The results illustrate comprehensive
MS/MS coverage for a set of complex small-molecule samples and demonstrate
a strong improvement on traditional DDA.

串联质谱（Tandem mass spectrometry, MS/MS）是极具价值的实验工具，可为基于质谱的“组学”实验中小分子与肽类的鉴定工作提供分析数据支撑。
数据依赖型MS/MS（Data-dependent MS/MS, DDA）是一种可响应特定样品中检测信号的实时MS/MS采集策略。然而，即便使用最先进的仪器分析中等复杂度的样品，MS/MS的采集速度仍不足以实现对所有检测到的分子的全面MS/MS覆盖。
数据非依赖型采集方法（Data-independent approaches, DIA）可实现更高的MS/MS覆盖度，但通常会以牺牲选择性或灵敏度为代价。
本报告介绍了数据集依赖型MS/MS（Dataset-dependent MS/MS, DsDA）——一种融合MS1数据处理与靶点优先级排序的全新方法，可在初始质谱级实验中实现全面的MS/MS采样。该方法的设计理念基于以下前提：在组学实验中，单次进样通常属于更大规模样品集的一部分，数据处理与数据采集之间的反馈可实现MS/MS采集参数的近似实时优化，进而达成近乎完整的MS/MS采样覆盖度。
研究团队结合使用R、Proteowizard、XCMS与WRENS软件，在液相色谱联用四极杆飞行时间质谱仪上验证了这一概念。
实验结果表明，该方法可为一系列复杂小分子样品实现全面的MS/MS覆盖，且相较传统DDA方法实现了显著性能提升。