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段的鉴定提供分析数据支持。数据依赖型MS/MS（Data-dependent MS/MS，DDA）是一种可响应给定样本中检测到的信号的实时MS/MS采集策略。然而，即便使用最先进的仪器设备分析中等复杂程度的样本，MS/MS的采集速度仍不足以实现对所有检测分子的全覆盖MS/MS分析。数据非依赖型采集策略（Data-independent approaches，DIA）可实现更高覆盖率的MS/MS分析，但通常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）——一种将MS1级数据处理与靶点优先级排序相结合的全新方法，可在初始MS级实验中实现全覆盖的MS/MS采样。该方法的设计理念基于组学实验的实际场景：单次进样通常属于更大规模的样本集，数据处理与数据采集之间的反馈机制可实现MS/MS采集参数的近似实时优化，并达成近乎全覆盖的MS/MS采样覆盖。
本研究结合R、Proteowizard、XCMS及WRENS软件工具，在液相色谱联用四极杆飞行时间质谱仪上实现了该方法。实验结果表明，该方法可实现复杂小分子样本集的全覆盖MS/MS分析，且相较传统DDA方法具有显著性能提升。