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.