Recent methodological developments in data-dependent analysis and data-independent analysis workflows for exhaustive lipidome coverage

Abstract

Untargeted lipidomics applied to biological samples typically involves the coupling of separation methods to high-resolution mass spectrometry (HRMS). Getting an exhaustive coverage of the lipidome with a high confidence in structure identification is still highly challenging due to the wide concentration range of lipids in complex matrices and the presence of numerous isobaric and isomeric species. The development of innovative separation methods and HRMS(/MS) acquisition workflows helped improving the situation but issues still remain regarding confident structure characterization. To overcome these issues, thoroughly optimized MS/MS acquisition methods are needed. 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 Data Dependent Acquisition (DDA) and Data Independent Acquisition (DIA). In this context, this perspective paper presents the latest developments of DDA- and DIA-based lipidomic workflows and lists available bioinformatic tools for the analysis of resulting spectral data.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

“…Several studies highlight the loss of 2‐5x sensitivity when using DIA versus DDA or full scan modes 131–133 . For more information, the following reviews are recommended 129,131,134 …”

“…[131][132][133] For more information, the following reviews are recommended. 129,131,134 Based on information from discovery experiments and/or literature, targeted lipidomics experiments can be performed, where a pre-defined set of lipids with a known m/z of precursor and product ions are analysed in a quantitative manner across large sample sets. Here, selected or multiple reaction monitoring (SRM/MRM) on triple quadrupole instrumentation, and recently parallel reaction monitoring (PRM) on quadrupole time-of-flight and orbitraps are employed.…”

Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data

“…Data-independent acquisition (DIA) is a mass spectrometry (MS) acquisition mode that systematically fragments precursor ions within a specific mass-to-charge ratio ( m/z ) range. It has the advantage of detecting low-abundance metabolites, which are often overlooked by conventional data-dependent acquisition (DDA) methods, due to their unavoidable loss of MS data coverage [ 5 , 6 ]. MS E , developed by Waters™ for Quadrupole Time of Flight (Q-TOF) MS analyzers, is a DIA method that fragments all precursor ions within the entire acquisition window by alternating between low- and high-collision energies, thereby obtaining consecutive scans of precursors and their fragments.…”

“…This unbiased tandem MS approach is therefore considered DIA due to its unbiased fragmentation of precursors, irrespective of their abundance [ 7 , 8 ]. The terms MS all and all-ion fragmentation (AIF) have been also employed for a similar type of fragmentation with Orbitrap analyzer-based instruments from Thermo Fisher™ [ 5 , 7 , 9 ].…”

Concomitant investigation of crustacean amphipods lipidome and metabolome during molting stage by Zeno SWATH Data-Independent Acquisition coupled with Electron Activated Dissociation and machine learning

“…SWATH guarantees comprehensive acquisition of a wide range of compounds in complex biological samples, as each precursor is assigned to a reconstructed fragmentation spectrum. While SWATH has demonstrated its efficacy in proteomics [7][8][9], it has also been recently explored in the field of metabolomics [10][11][12] and applied to lipidomics [13,14].…”