Developing Multidimensional Skyline Spectral Libraries for Rapid Lipid Analysis

Multidimensional measurements integrating liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS) provide valuable polarity, structural and mass information simultaneously for lipidomic analyses and show tremendous power for attaining more confident lipid identifications. For all of their advantages, LC-IMS-MS measurements are highly complex and result in huge datasets which are difficult to process in a timely fashion. Thus, developing a data analysis workflow that is capable of accurate and rapid molecular analyses is essential.

The freely available, open-source software Skyline offers targeted processing of lipid data which ultimately allows for confident identification of diverse lipid species. We have developed sample-specific lipid spectral libraries which include over 700 target lipids from multiple lipid categories. Each target lipid is populated with m/z values, normalized retention times, ion mobility collision cross section (CCS) values, and known fragmentation patterns. These values were manually extracted from LC-IMS-MS experimental data and verified using existing literature.

Recently developed aspects of the Skyline small molecule interface are utilized in this workflow including IMS spectrum filtering and retention time prediction (iRT) using a set of ~20 endogenous lipids for gradient correction and LC alignment. Application of lipid CCS value filtering further increased lipid annotation confidence and greatly improved the signal to noise ratio for the target species. These lipid spectral libraries will be made publically available through Skyline’s online repository Panorama after additional validation studies.

For Research Use Only. Not for use in diagnostic procedures.

Presenter: Kaylie Kirkwood (NC State University Graduate Student, Baker Lab - Department of Chemistry, NC State University)

Kaylie Kirkwood is a second-year chemistry PhD student in Dr. Erin Baker’s lab at North Carolina State University (NCSU). Thus far, her research has been focused on the development of multidimensional lipid spectral libraries for the rapid and confident identification of lipid species in complex samples. This work is essential for current and future applications in the Baker lab and the broader lipidomics community. Kaylie studies both clinical and environmental applications ranging from elucidating lipid markers associated with smoke inhalation injury to evaluating lipid dysregulation following exposure to perfluoroalkyl substances (PFAS). She is a trainee in the NIH/NCSU Molecular Biotechnology Training Program and is currently serving as the Communications Committee Chair of Females in Mass Spectrometry (FeMS). Prior to graduate school, Kaylie completed a B.S. in chemistry with a minor in biological sciences at NCSU. As an undergraduate researcher in Dr. David Muddiman’s lab, she utilized capillary electrophoresis-mass spectrometry for the measurement of small molecules associated with neurodegenerative diseases.