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

Abstract

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.