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Updated: May 8, 2026

Tracing de novo Lipids using Stable Isotope Labeling LC-TIMS-TOF MS/MS
Published on: August 23, 2024
Enhanced data-independent analysis of lipids using ion mobility-TOFMSE to unravel quantitative and qualitative
Vinit Shah1, Jose M Castro-Perez, David G McLaren
1Analytical Biochemistry and Molecular Biomarkers, Merck Research Laboratories, Kenilworth, NJ 07033, USA. vinit_shah2@merck.com
Rationale:
Lipids are involved in various biochemical and signaling pathways, cell structure and function, and the pathophysiology of many diseases. We took advantage of ion mobility spectrometry (IMS) in conjunction with ultra-performance liquid chromatography (UPLC) and high-resolution mass spectrometry to gain quantitative and deeper qualitative structural insight within a single experiment.
Methods:
Human plasma lipid extracts were analyzed using an Acquity UPLC system coupled to a Synapt G2-HDMS mass spectrometer system. The ion mobility gas employed was helium for the helium cell (150 mL/min) and nitrogen (80 mL/min) for the T-wave drift tube. The wave height for the T-wave cell was ramped in a linear fashion between 5-40 V. The mass spectra were acquired in an electrospray positive ionization mode.
Results:
We resolved chromatographically co-eluting lipids further by ion mobility tube drift time and then subjected them to low- and high-energy fragmentation without pre-selecting respective precursor species. The fragment ions produced in a high-energy mode were aligned with their precursor ions in a low-energy mode. By aligning intact molecular spectra and fragment spectra for these lipids at a given ion mobility drift time and chromatographic retention time, we were able to obtain much cleaner fragment ion spectra for structural elucidation. For quantitative analysis we obtained a dynamic linear range from 0.002 to 2 µg/mL with and without an additional dimension of IMS.
Conclusions:
The additional dimension of IMS allowed us to perform quantitative and qualitative analysis within a single experiment in a relatively high-throughput manner thus providing deeper structural insights into lipids of biological interest and resulting in an information-rich dataset.
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