Large-Scale Lipid Profiling of a Human Serum Lipidome Using a High-Resolution, Accurate-Mass LC/MS/MS Approach

Importance of the Topic

Lipidomics profiling is a powerful tool for discovering disease biomarkers and understanding metabolic pathways. The lipidome's complexity, with thousands of species and many isomeric forms, demands high chromatographic and mass spectrometric resolution. Improved lipid identification and quantification support early disease detection, personalized medicine, and quality control in research and industry.

Objectives and Study Overview

This study aimed to develop a robust high-resolution accurate-mass LC-MS workflow for comprehensive lipid profiling of human serum and plasma. Key goals included enhanced separation of lipid isomers, expanded lipid identification coverage, rapid throughput, and reliable relative quantification across complex biological samples.

Experimental Methodology and Used Instrumentation

Sample Preparation and Extraction

• Serum and plasma samples from donors under different dietary conditions and a pooled plasma reference were extracted using a chloroform-methanol-water protocol with internal standards for major lipid classes.
• Extracts were dried and reconstituted in isopropanol/methanol for LC-MS analysis.

Chromatography

• Thermo Scientific Dionex UltiMate 3000 RSLC system.
• Acclaim C30 UHPLC column, 2.1 × 250 mm, 1.9 μm, at 45 °C.
• Gradient of acetonitrile/water and isopropanol/acetonitrile with ammonium formate and formic acid, 200 μL/min flow, 2 μL injection.

Mass Spectrometry

• Thermo Scientific Q Exactive HF hybrid quadrupole-Orbitrap with HESI-II probe.
• Full-scan MS at 120,000 resolving power, sub-3 ppm mass accuracy.
• Data-dependent Top15 MS/MS at 30,000 resolution, stepped collision energy, positive and negative modes.

Data Processing

• LipidSearch software version 4.1 for automated identification, using 5 ppm mass tolerances and class-specific adduct filters.
• Alignment across sample runs, retention window of ±0.1 min, quality filters to reduce false positives.

Key Findings and Discussion

Isomer Separation

• C30 column resolved 14 TG(55:3) isomers compared to five on a C18 column under similar conditions, demonstrating superior shape selectivity for geometric isomers.

Lipid Identification Coverage

• Approximately 973 lipid species, including multiple isomers, were identified across eight major lipid classes in human serum and plasma.

Quantitative Performance

• Relative quantitation showed coefficients of variation below 15% for most lipids across triplicate runs.
• Targeted analysis of TG 54:6 isomers achieved CVs under 7% with deuterated TG internal standard calibration.

Biological Insights

• PCA demonstrated clear grouping of serum from donors with different dietary supplements based on molecular lipid profiles.
• Flaxseed oil supplementation was associated with higher levels of polyunsaturated TG species, while fish oil intake altered specific long-chain TG abundances.

Benefits and Practical Applications

This workflow offers high molecular resolution, deep coverage of the lipidome, rapid data acquisition, and robust quantitation, making it suitable for:

• Clinical biomarker discovery and monitoring.
• Quality control in pharmaceutical and nutritional research.
• Comparative lipidomics in disease and wellness studies.

Future Trends and Potential Applications

Advances in column chemistry and Orbitrap speed will further enhance isomer separation. Integration of ion mobility and machine learning–based data analysis may streamline lipid annotation. Expansion to single-cell lipidomics and in vivo imaging applications will broaden the utility of high-resolution lipid profiling in systems biology and precision medicine.

Conclusion

A high-resolution accurate-mass LC-MS workflow combining a C30 UHPLC column, Q Exactive HF Orbitrap, and LipidSearch software enables comprehensive identification and quantification of nearly a thousand lipid species from human serum/plasma in a single run. The method demonstrates excellent isomer resolution, analytical precision, and throughput for large-scale lipidomics studies.

References

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