Fully Automatized Detection of Phosphocholine-Containing Lipids through an Isotopically Labeled Buffer Modification...

Area of Science:

• Analytical Chemistry
• Biochemistry
• Mass Spectrometry

Background:

• High-resolution mass spectrometry is crucial for lipidomics.
• Current LC-MS methods for polar lipids face challenges with isobaric and isomeric mass overlaps, hindering accurate identification.
• Existing software often misannotates lipid species due to these overlaps.

Purpose of the Study:

• To develop and optimize a buffer modification workflow for enhanced polar lipid identification in human plasma.
• To improve the accuracy and reduce the false-positive rate in lipidomics data analysis.
• To provide a more robust and user-friendly alternative to existing lipid annotation platforms.

Main Methods:

• Optimization of a buffer modification workflow using labeled and unlabeled acetate ions via Box-Behnken design.
• Application of the workflow to phosphocholine-containing lipids in human plasma samples.
• Utilizing [M + CH3COO]-, [M + CD3COO]-, and [M - CH3]- adducts with a dedicated data processing workflow on Compound Discoverer software.

Main Results:

• Successfully determined adduct composition, molecular formulas, and grouping for phosphocholine lipids.
• Achieved a lower false-positive rate compared to commonly employed lipidomics platforms.
• Streamlined the manual validation step in lipidomics data analysis.

Conclusions:

• The proposed buffer modification workflow offers a robust and simplified approach for improving lipid annotation accuracy.
• This method does not necessitate extensive sample pretreatment, isotopic enrichment, or derivatization.
• Represents a significant advancement for qualitative and quantitative lipidomics analyses.