Computational mass spectrometry accelerates C = C position-resolved untargeted lipidomics using oxygen attachment dissociation

MS-DIAL 5 multimodal mass spectrometry data mining unveils lipidome complexities

Lipidomics and metabolomics communities comprise various informatics tools; however, software programs handling multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 for in-depth lipidome structural elucidation through electron-activated dissociation (EAD)-based tandem MS and determining their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section values. With the optimized EAD settings using 14 eV kinetic energy, the program correctly delineated lipid structures for 96.4% of authentic standards, among which 78.0% had the sn-, OH-, and/or C = C positions correctly assigned at concentrations exceeding 1 μM. We showcased our workflow by annotating the sn- and double-bond positions of eye-specific phosphatidylcholines containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and n-3-VLC-PUFA-supplemented HeLa cells, we identified glycerol 3-phosphate acyltransferase as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into the sn1 position of phospholipids in mammalian cells, which was confirmed using EAD-MS/MS and recombinant proteins in a cell-free system. Therefore, the MS-DIAL 5 environment, combined with optimized MS data acquisition methods, facilitates a better understanding of lipid structures and their localization, offering insights into lipid biology.

Aza-Prilezhaev Aziridination-Enabled Multidimensional Analysis of Isomeric Lipids via High-Resolution U-Shaped Mobility Analyzer-Mass Spectrometry

Unsaturated lipids constitute a significant portion of the lipidome, serving as players of multifaceted functions involving cellular signaling, membrane structure, and bioenergetics. While derivatization-assisted liquid chromatography tandem mass spectrometry (LC-MS/MS) remains the gold standard technique in lipidome, it mainly faces challenges in efficiently labeling the carbon-carbon double bond (C═C) and differentiating isomeric lipids in full dimension. This presents a need for new orthogonal methodologies. Herein, a metal- and additive-free aza-Prilezhaev aziridination (APA)-enabled ion mobility mass spectrometric method is developed for probing multiple levels of unsaturated lipid isomerization with high sensitivity. Both unsaturated polar and nonpolar lipids can be efficiently labeled in the form of N-H aziridine without significant side reactions. The signal intensity can be increased by up to 3 orders of magnitude, achieving the nM detection limit. Abundant site-specific fragmentation ions indicate C═C location and sn-position in MS/MS spectra. Better yet, a stable monoaziridination product is dominant, simplifying the spectrum for lipids with multiple double bonds. Coupled with a U-shaped mobility analyzer, identification of geometric isomers and separation of different lipid classes can be achieved. Additionally, a unique pseudo MS3 mode with UMA-QTOF MS boosts the sensitivity for generating diagnostic fragments. Overall, the current method provides a comprehensive solution for deep-profiling lipidomics, which is valuable for lipid marker discovery in disease monitoring and diagnosis.

LipidOz enables automated elucidation of lipid carbon-carbon double bond positions from ozone-induced dissociation mass spectrometry data

Lipids play essential roles in many biological processes and disease pathology, but unambiguous identification of lipids is complicated by the presence of multiple isomeric species differing by fatty acyl chain length, stereospecifically numbered (sn) position, and position/stereochemistry of double bonds. Conventional liquid chromatography-mass spectrometry (LC-MS/MS) analyses enable the determination of fatty acyl chain lengths (and in some cases sn position) and number of double bonds, but not carbon-carbon double bond positions. Ozone-induced dissociation (OzID) is a gas-phase oxidation reaction that produces characteristic fragments from lipids containing double bonds. OzID can be incorporated into ion mobility spectrometry (IMS)-MS instruments for the structural characterization of lipids, including additional isomer separation and confident assignment of double bond positions. The complexity and repetitive nature of OzID data analysis and lack of software tool support have limited the application of OzID for routine lipidomics studies. Here, we present an open-source Python tool, LipidOz, for the automated determination of lipid double bond positions from OzID-IMS-MS data, which employs a combination of traditional automation and deep learning approaches. Our results demonstrate the ability of LipidOz to robustly assign double bond positions for lipid standard mixtures and complex lipid extracts, enabling practical application of OzID for future lipidomics.

MS-RIDD paves the way toward routine double bond localization in mass spectrometry-based lipidomics

Pinpointing double bond (C=C) positions in native lipid extracts is beyond the capabilities of standard mass spectrometry-based approaches. This article highlights a novel untargeted workflow supported by the open-source software MS-RIDD, that allows for semi-automated annotation of C=C locations with high confidence.