Retrospective metabolomics via dual-dimensional deconvolution using ZT Scan DIA 2.0

Herein, we present a scanning data-independent acquisition (DIA) approach (ZT Scan DIA 2.0) combined with dual-dimensional tandem mass spectrometry spectral filtering and deconvolution along both the quadrupole and retention time axes to reconstruct compound-specific MS2 spectra from complex mixtures. This approach outperformed conventional data-dependent acquisition (DDA) and window-based DIA methods in terms of annotation rates for hydrophilic metabolomics (114-160%) and lipidomics (105- 136%). Moreover, this approach achieved dot product score distributions comparable with those obtained with a 1-Da precursor isolation window. Furthermore, the platform enables lipid isomer separation through the retrospective analysis of complete DIA datasets covering 1,017 and 2,353 molecules for human plasma and mouse liver tissues, respectively. In addition, the platform yields compound-specific ground truth MS2 spectra that surpass DDA in terms of spectral purity. This establishes a transformative foundation for repository-scale metabolomics in line with the findable, accessible, interoperable, and reusable data principles.