A multimodal measurement platform for unambiguous lipid identification

The National Institute of General Medical Sciences awarded $1.688 million to Pacific Northwest National Laboratory, a division of Battelle Memorial Institute, on August 1, 2026, under the Biomedical Research and Research Training program (CFDA 93.859) to develop a multimodal measurement platform for unambiguous lipid identification.

The recipient will build a high-resolution ion mobility-mass spectrometry (IM-MS) system designed to distinguish free fatty acids and lipid isomers in complex biomedical samples. The platform combines a novel traveling-cups ion mobility module (cupped IMS) to separate structurally similar lipid isomers with collision cross-section measurements, and ultraviolet photodissociation capability integrated into an Orbitrap mass spectrometer to identify the locations of lipid double bonds along alkyl chains. High-resolution mass measurements from the Orbitrap will derive chemical formulae for lipids and free fatty acids. The system addresses a gap in lipidomics research by unambiguously characterizing lipid signatures whose biomedical activities remain unknown due to current analytical technology's inability to distinguish isomers.

The award covers the period from August 1, 2026, through July 31, 2030, with place of performance in Washington. NIGMS supports basic research that increases understanding of biological processes and lays the foundation for advances in disease diagnosis, treatment, and prevention.

Abstract

Free fatty acids (ffas) and lipids are important biological compounds that are involved in almost every biological process. Studying the lipidome can provide information on the roles of lipids, ranging from nutrient absorption and cell signaling to cancer metastasis. However, identifying the complete chemical structures of many lipids is a long-standing analytical challenge. Lipids possess an enormous number of isoforms (compounds with the same chemical formula but different arrangements of atoms), but current analytical technology struggles to distinguish many of them. This means many lipid signatures remain uncharacterized and their biomedical activities remain unknown. This project will address this significant GAP in lipidomics research by developing a novel multimodal system that will be used to unambiguously identify ffas and lipids in complex biomedically- relevant samples. This will be accomplished by using a novel high-resolution ION mobility-mass spectrometry (IM-MS) platform employing two different types of fragmentation. A novel high-resolution IM module based on 'traveling cups' (termed cupped IMS) will provide new state-of-the-art IM separations of FFA and lipid isomers, many of which are notoriously difficult to separate due to their high structural similarity. Collision cross section (CCS) measurements gained from such HR-IMS separations will provide a key physical metric by which to differentiate these structurally similar ffas and lipids. A new ultraviolet photodissociation capability will be installed into an orbitrap mass spectrometer to provide information on the locations of lipid double bonds along alkyl chains, which is often missing in gold-standard MS-based workflows. The orbitrap-MS will also provide high-resolution mass measurements, which can be used to derive the chemical formulae of ffas and lipids. Having chemical formula information is an essential first step when beginning to determine the structure of an unknown lipid. The orbitrap will also provide collision induced dissociation capabilities, which are useful for identifying to which class of lipids an unknown compound belongs. New data-dependent acquisition (DDA) and data-independent acquisition (DIA) methods will be developed to enable automated acquisition of MS/MS spectra from the new multimodal system, and informatics workflows will be developed to leverage data processing software already capable of reading thermo-fisher .raw files. A novel uvpd informatics capability will be developed to interpret the multimodal data from this new system. The data will be benchmarked against gold-standard LC-MS/MS lipidomics workflows to show significantly improved lipid identifications from lipid extracts of hela cells, which has tremendous implications in diseases like breast cancer. The discoveries made by the multimodal system proposed here will significantly advance the field of lipidomics research. Furthermore, this research will show that multimodal systems are critical tools that will one day be used in general structural identification workflows where reference data from authentic compounds are not available.