LipidQuan: Quantifying the Lipidome of Transgenic Mice Tissue Extracts, a Rapid and Comprehensive Targeted Approach

Importance of the Topic

The lipidome influences membrane structure, signaling pathways, and metabolic homeostasis. Efficient quantification of diverse lipids is critical for understanding disease mechanisms and evaluating metabolic phenotypes.

Objectives and Study Overview

This study applies the LipidQuan targeted workflow to quantify approximately 500 lipid species in murine adipose tissue. The goal is to compare wild-type and LRG1 knockout mice to uncover lipidomic changes resulting from the absence of a candidate adipokine.

Methodology

Adipose tissue (~30 mg) was extracted via a chloroform:methanol (2:1) Bligh and Dyer protocol. Samples were reconstituted in isopropanol, spiked with stable isotope-labeled standards, and randomized. Dual-mode (positive/negative) multiple reaction monitoring (MRM) acquisition targeted both headgroup and fatty acyl fragment transitions for enhanced specificity. Calibration curves spanning four orders of magnitude were generated using pooled QC samples at multiple concentration levels. Data processing employed TargetLynx or Skyline, with subsequent statistical evaluation by SIMCA P+ and MetaboAnalyst.

Instrumentation Used

• ACQUITY UPLC I-Class PLUS (or H-Class) with BEH Amide 2.1 × 100 mm, 1.7 µm column
• Xevo TQ-XS, TQ-S, or TQ-S micro mass spectrometers with ESI source (positive/negative)
• TargetLynx Application Manager and Quanpedia for method deployment
• MassLynx Software for acquisition control
• SIMCA P+ and MetaboAnalyst for multivariate and univariate analysis

Main Results and Discussion

The LipidQuan workflow identified over 400 lipid species, including phosphatidylcholines, plasmalogens, sphingomyelins, glycerophospholipids, and neutral lipids. HILIC separation facilitated class-based elution and improved resolution of isobaric/isomeric species by combining retention time with fatty acyl fragment MRMs. Partial least squares discriminant analysis achieved Q2 ≈ 0.9, clearly separating wild-type and knockout cohorts. VIP scoring and hierarchical clustering highlighted LPC, PC plasmalogens, and SM as major discriminants. Several plasmalogen PCs (e.g., PC(18:1e/16:0)) were elevated in knockout tissue, whereas specific sphingomyelins were decreased. Calibration curves of deuterated internal standards exhibited high linearity (R2 ≥ 0.97), supporting accurate quantification.

Benefits and Practical Applications

This method offers an eight-minute LC-MS/MS runtime with reduced stable isotope requirements, lowering cost and simplifying training. Prebuilt MRM libraries via Quanpedia streamline method setup and reduce transcription errors. The workflow is well suited for QA/QC laboratories, biomarker discovery, and preclinical metabolic research applications.

Future Trends and Applications

Integration with high-resolution mass spectrometry and expanded MRM libraries will further enhance isomer discrimination. Coupling with spatial lipidomics and automated data analytics pipelines can enable real-time monitoring of metabolic states in clinical and industrial settings.

Conclusion

LipidQuan delivers a rapid, robust, and cost-effective targeted lipidomics platform, demonstrated by clear lipidomic alterations in LRG1 knockout mice. Its scalability and ease of deployment support broad adoption in both research and quality-control environments.

Reference

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