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

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 for enzyme preference, cellular membrane milieu, and biological activity, the C=C defined structures have not yet been characterized. Here, we present a novel approach for C=C position-resolved untargeted lipidomics using a combination of oxygen attachment dissociation and computational mass spectrometry to increase the rate of annotation. We validated the accuracy of our platform as per the authentic standards of 21 lipid subclasses and the biogenic standards of 51 molecules containing polyunsaturated fatty acids (PUFAs) from the cultured cells fed with various fatty acid-enriched media. By analyzing human and mice-derived biological samples, we characterized 675 unique lipid structures with the C=C position-resolved level encompassing 22 lipid subclasses defined by LIPID MAPS. Our platform also illuminated the unique profiles of tissue-specific lipids containing n-3 and/or n-6 very long-chain PUFAs (carbon M 28 and double bonds a 4) in the eye, testis, and brain of the mouse.