PT - JOURNAL ARTICLE AU - Catherine G. Vasilopoulou AU - Karolina Sulek AU - Andreas-David Brunner AU - Ningombam Sanjib Meitei AU - Ulrike Schweiger-Hufnagel AU - Sven Meyer AU - Aiko Barsch AU - Matthias Mann AU - Florian Meier TI - Trapped ion mobility spectrometry (TIMS) and parallel accumulation - serial fragmentation (PASEF) enable in-depth lipidomics from minimal sample amounts AID - 10.1101/654491 DP - 2019 Jan 01 TA - bioRxiv PG - 654491 4099 - http://biorxiv.org/content/early/2019/05/31/654491.short 4100 - http://biorxiv.org/content/early/2019/05/31/654491.full AB - Lipids form a highly diverse group of biomolecules fulfilling central biological functions, ranging from structural components to intercellular signaling. Yet, a comprehensive characterization of the lipidome from limited starting material, for example in tissue biopsies, remains very challenging. Here, we develop a high-sensitivity lipidomics workflow based on nanoflow liquid chromatography and trapped ion mobility spectrometry. Taking advantage of the PASEF principle (Meier et al., PMID: 26538118), we fragmented on average nine precursors in each 100 ms TIMS scans, while maintaining the full mobility resolution of co-eluting isomers. The very high acquisition speed of about 100 Hz allowed us to obtain MS/MS spectra of the vast majority of detected isotope patterns for automated lipid identification. Analyzing 1 uL of human plasma, PASEF almost doubled the number of identified lipids over standard TIMS-MS/MS and allowed us to reduce the analysis time by a factor of three without loss of coverage. Our single-extraction workflow surpasses the plasma lipid coverage of extensive multi-step protocols in common lipid classes and achieves attomole sensitivity. Building on the high precision and accuracy of TIMS collisional cross section measurements (median CV 0.2%), we compiled 1,327 lipid CCS values from human plasma, mouse liver and human cancer cells. Our study establishes PASEF in lipid analysis and paves the way for sensitive, ion mobility-enhanced lipidomics in four dimensions.