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

Abstract

Mass spectrometry-based untargeted lipidomics has revealed the lipidome atlas of living organisms at the molecular species level. Despite the double bond (C = C) position being a crucial factor in biological system, the C = C defined structures have not yet been characterized comprehensively. Here, we present an approach for C = C position-resolved untargeted lipidomics using a combination of oxygen attachment dissociation and computational mass spectrometry to increase the annotation rate. We validated the accuracy of our platform as per the authentic standards of 85 lipids and the biogenic standards of 52 molecules containing polyunsaturated fatty acids (PUFAs) from the cultured cells fed with various fatty acid-enriched media. By analyzing human and mice-derived samples, we characterized 648 unique lipids with the C = C position-resolved level encompassing 24 lipid subclasses defined by LIPIDMAPS. Our platform also illuminated the unique profiles of tissue-specific lipids containing n-3 and/or n-6 very long-chain PUFAs (carbon $$\ge$$ ≥ 28 and double bonds $$\ge$$ ≥ 4) in the eye, testis, and brain of the mouse.

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

“…To provide computational means for C=C position annotation, Arita et al 6 developed the tool named mass spectrometry radical-induced dissociation decipherer (MS-RIDD), an open-source software tailored to a promising untargeted analysis strategy for complex biological samples. MS-RIDD owes its name to the fragmentation technique it was devised for: oxygen attachment dissociation (OAD) 7 , which belongs to the group of radical-induced fragmentation methods.…”

“…However, OAD rarely reveals ions characteristic of intact hydrophobic lipid chains, which are required for lipid molecular species identification. To overcome this drawback, Arita and colleagues 6 deftly devised a strategy that incorporates both CID spectra (in both polarities) and OAD spectra (positive ion mode) in one analytical workflow. The CID-related measurements reveal information up to the lipid molecular species level, which is further complemented by C = C position information obtained by OAD spectra.…”

“…To deal with the two types of MS data, Arita et al 6 integrated two computational tools in the analytical workflow (Fig. 2 ).…”

“…Accordingly, the exact number of preceding C=C is known, which allows for the annotation of most lipid species consisting of more than one unsaturated chain. In this context, Arita and colleagues 6 advise caution, as ambiguities may arise in the presence of cyclopropane-containing hydrocarbon chains since their OAD fragments are similar to those specific for C=C. Cases, where experimentally observed fragments result in ambiguous assignments, can be manually resolved on the basis of biological knowledge via a simple-to-use graphical user interface.…”

“…Remarkably, Arita et al 6 meticulously scrutinized the overall limitations of the composite workflow. They provide comprehensive data on the limit of detection (LOD) and limit of annotation measured based on a total of 79 authentic lipid standards encompassing 23 lipid subclasses since the fragmentation efficiency of C=C generally depends on several variables including the C=C position, lipid subclass, and adduct type.…”