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

Abstract

AbstractMass 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.