Accurate Sphingolipid Quantification Reducing Fragmentation Bias by Nonlinear Models

Area of Science:

• Lipidomics
• Biochemistry
• Metabolomics

Background:

• Quantitative sphingolipid analysis is vital for understanding cellular processes and diseases.
• Current methods using a single internal standard per sphingolipid class struggle with structural diversity.
• Fragmentation differences limit the accuracy of traditional sphingolipid quantification.

Purpose of the Study:

• To develop a novel, accurate, and versatile approach for quantitative sphingolipid analysis.
• To overcome the limitations of the "one standard per class" strategy in sphingolipidomics.
• To provide a user-friendly tool for precise sphingolipid measurements.

Main Methods:

• Utilized fragmentation models to correct for structural variations in sphingolipids.
• Developed an internal standard-independent quantification method.
• Integrated the novel approach into a KNIME workflow for accessibility.

Main Results:

• The new method accurately quantifies ceramide subclasses across diverse biological matrices.
• Demonstrated independence from internal standards, instrumental setup, and collision energy.
• Validated the effectiveness of the fragmentation model-based approach.

Conclusions:

• This novel approach significantly enhances the accuracy of sphingolipid quantification.
• The method offers a robust solution for analyzing sphingolipid metabolism.
• Opens new possibilities for research in sphingolipid-related physiology and pathology.