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Updated: Apr 25, 2026

Quantitative and Qualitative Method for Sphingomyelin by LC-MS Using Two Stable Isotopically Labeled Sphingomyelin Species
Published on: May 7, 2018
Direct Comparison of MRM-MS and PRM-MS Methods for Quantitative Ganglioside Analysis
Akeem Sanni1, Abderrahmane Koraich1, Judith Nwaiwu1
1Chemistry and Biochemistry Department, Texas Tech University, Lubbock, Texas 79409, United States.
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Gangliosides are structurally diverse, low-abundance glycosphingolipids central to neuronal signaling and cancer progression; however, their quantitative analysis is hindered by low ionization efficiency, structural heterogeneity, and complex isomeric patterns. Targeted mass spectrometry (MS) represents a powerful approach for resolving these challenges, yet systematic comparisons of multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) for native gangliosides remain limited. Here, we developed and optimized a targeted LC-MS/MS workflow to directly evaluate PRM on a Q-Exactive HF Orbitrap versus MRM on a TSQ Vantage triple quadrupole. Collision-energy optimization revealed distinct fragmentation behaviors across platforms, identifying optimal normalized collision energies (NCE) for PRM of 28 for GD1a and 25 for GD2, GT1b, GM1, and GQ1b, whereas optimal CE values for MRM were 35 for GD1a, GD2, and GT1b, and 30 for GQ1b. Additionally, PRM enabled multiplexing up to 15 transitions per analyte, improving signal-to-noise up to ∼4-fold and reducing %RSD through postacquisition transition summation. High-energy collision dissociation (HCD) used in PRM generated a richer array of fragment ions, including informative cross-ring cleavages and low-mass diagnostic ions, providing superior structural confidence compared to CID fragmentation in MRM. Notably, PRM uniquely enabled quantification of GM1, which exceeded the mass range of the triple quadrupole instrument. Applied to post-mortem human brain tissue extracts, PRM distinguished GD1a and GD1b isomers with high specificity. These findings establish PRM as a robust, highly sensitive, and structurally informative platform for comprehensive ganglioside profiling in complex biological matrices.

