Algorithm-Driven Chromatographic Method for Prostaglandin Isomer Identification via Tandem Mass Spectrometry

Area of Science:

• Analytical Chemistry
• Biochemistry
• Computational Chemistry

Background:

• Prostaglandins (PGs) are crucial lipid mediators with distinct biological roles.
• PG E2 (PGE2) and D2 (PGD2) are positional isomers that are difficult to differentiate using tandem mass spectrometry (MS/MS).
• Supercritical fluid chromatography (SFC) coupled with MS/MS is a powerful tool for PG analysis.

Purpose of the Study:

• To develop computational methods for isolating PG isomers, specifically PGE2 and PGD2.
• To enhance method development efficiency for Supercritical Fluid Extraction (SFE) and SFC-MS/MS.
• To gain insights into PG retention behavior in SFE/SFC-MS/MS.

Main Methods:

• Utilized selected reaction monitoring (SRM)-based techniques for isomer differentiation.
• Employed least-squares estimation to solve a linear system for abundance ratio determination.
• Investigated factors influencing PG retention, including stationary phase, temperature, and matrix effects.

Main Results:

• Successfully differentiated coeluting PGE2 and PGD2 isomers computationally, despite challenges with baseline resolution.
• Achieved precise quantification of PGE2 to PGD2 abundance ratios from intensity ratios across four SRM transitions.
• Identified concentration-dependent entrainer suppression effects and critical factors for PG retention.

Conclusions:

• Computational isolation and SRM-based techniques enable high-throughput PG analysis without complete chromatographic resolution.
• Findings contribute to developing robust analytical platforms for PG quantification in lipidomics.
• Effective matrix management is crucial for accurate SFE/SFC-MS/MS analysis of PGs.