Recent methodological developments in data-dependent analysis and data-independent analysis workflows for exhaustive lipidome coverage - Valmori, Marie; Marie, Vincent; Fenaille, François; Colsch, Benoit; Touboul, David (Frontiers in Analytical Science, 2023)
Untargeted lipidomics applied on biological samples, typically analyzed by hyphenated-based techniques coupled to high resolution mass spectrometry (HRMS), encountered the issue of the wide dynamic range of lipids in those complex matrices. Since elucidating structure of biomarkers relies on separative parameters, MS and MS/MS spectral data, acquisition represents the major point to identify molecular lipid species. Even if innovations in separative methods coupled to HRMS contribute to new perspectives in lipidomics, various issues remain, such as structural diversity, coelution, isobaric and isomeric compounds. To overcome these issues, one of the keys is to optimize MS/MS acquisition methods. For this purpose, different methodologies have been developed to enable MS and MS/MS acquisition in parallel. Those methodologies, derived from the proteomics, are referred to as the Data Dependent Acquisition (DDA) and Data Independent Acquisition (DIA). In this context, this perspective presents the novel development for the DDA- and DIA-based workflows used for lipidomics and lists the available bioinformatic tools developed for the spectral data analysis.