CRB-SWATH: A Method for Enhancing Untargeted Precursor Ion Extraction and Automatically Constructing Their Tandem Mass Spectra from SWATH Datasets by Chromatographic Retention Behaviors

Sequential
window acquisition of all theoretical spectra (SWATH)
as a typical data-independent acquisition (DIA) strategy is favorable
for untargeted metabolomics. It could theoretically acquire product
ions of all precursor ions, including precursor ions showing chromatographic
peaks of rather poor qualities. However, existing data processing
methods present limited capabilities in capturing poor-quality peaks
of precursor ions. Thus, although their product ions could be acquired,
their precursor ions are absent. Here, we present a new strategy,
chromatographic retention behavior-SWATH (CRB-SWATH), that could unbiasedly
capture poor-quality peaks and provide high resolutions of multiplexed
mass spectroscopy (MS/MS) spectra in SWATH datasets. CRB-SWATH monitors
CRBs of SWATH-MS signals under a series of altered elution gradients.
As signals of compounds differ from noise by showing CRBs, both the
precursor and fragment ions are captured, while ignoring their peak
qualities. Moreover, CRB-SWATH offers good chances to resolve highly
multiplexed MS/MS spectra in SWATH datasets because precursor ions
coeluted in a single elution gradient often present different CRBs.
In the untargeted metabolic analysis of Hela cell
extracts, CRB-SWATH showed the advantage in exclusively capturing
2645 ions of poor-quality peaks (i.e., tiny peaks, discontinuous ion
traces, tailing peaks, zigzag peaks, etc.), accounting for 34.4% of
all the untargeted precursor ions extracted. Therein, it is noteworthy
that among 2116 negative ions detected in hydrophilic interaction
liquid chromatography (HILIC) mode, 1284 poor-quality ion peaks (>60%)
were exclusively captured by CRB-SWATH. As CRB-SWATH automatically
captures a large sum of true ion peaks of poor qualities, extracts
MS/MS spectra of high purities, and provides chromatographic retention
behaviors of untargeted metabolites for identification and classification,
it could be a useful metabolomics tool for understanding biological
phenomena better.