Keio University

Development of a New Structural Analysis Method to Identify the Double Bond Positions in Lipids: Contributing to the Elucidation of Lipid Metabolism Mechanisms with Mass Spectrometry and Data Science

Publish: December 19, 2022
Public Relations Office

December 19, 2022

RIKEN

Keio University

Japan Science and Technology Agency

A joint research team—led by Haruki Uchino, a graduate student research associate (fourth-year Doctoral Programs student at the Keio University Graduate School of Pharmaceutical Sciences); Yuji Tsugawa, a visiting researcher (tenure-track associate professor at the Institute of Global Innovation Research, Tokyo University of Agriculture and Technology); and Makoto Arita, team leader (professor at the Keio University Faculty of Pharmacy and Graduate School of Pharmaceutical Sciences) from the RIKEN Center for Integrative Medical Sciences, Laboratory for Metabolomics—has developed a new non-targeted lipidomics technology that can unbiasedly and comprehensively determine the positions of carbon-carbon double bonds (C=C), which are crucial for understanding the physiological functions of lipids.

This research outcome clearly identifies fatty acid side-chain information, such as that of omega-3 and omega-6, which has been difficult to analyze with conventional methods. It is expected to contribute to elucidating the structural diversity of lipids and understanding the pathological mechanisms associated with abnormal lipid metabolism.

The joint research team has now established an analytical technique using Oxygen Attachment Dissociation (OAD), a fragmentation method that causes dissociation specific to C=C positions, to enable the analysis of C=C positions by mass spectrometry. Next, by analyzing in detail the tandem mass spectrometry (MS/MS) data (OAD-MS/MS spectra) of 85 lipid standards obtained using this technique and formulating rules for their dissociation mechanisms, the team developed "MS-RIDD," a software for analyzing complex OAD-MS/MS data. Applying this technology to the lipid analysis of actual biological samples, such as human and mouse tissues, they successfully determined the lipid structures, including the C=C positions, of a total of 648 molecular species. These lipid structures included many C=C positions that could not be determined by conventional methods, demonstrating the effectiveness of this newly developed technology.

This research was published in the online edition of the scientific journal "Communications Chemistry" on December 19.

Please see below for the full press release.

Press Release (PDF)