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Related Experiment Video

Updated: May 26, 2026

Shotgun Lipidomics of Rodent Tissues

Shotgun Lipidomics of Rodent Tissues

Published on: November 18, 2022

Tissue Heterogeneity-Driven Parallel Acquisition for High-Coverage MS/MS Imaging of Lipids.

Dan Li¹, Yao Qian¹, Aolei Tan¹

¹Department of Precision Instrument, State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China.

Angewandte Chemie (International Ed. in English)

|May 25, 2026

Summary

This summary is machine-generated.

A new method, Deconvolution-based Structure-Specific Spatial Lipidomics (DeconS2L), enables high-resolution lipidomics imaging. This technique enhances lipid analysis in tissues, aiding biomarker discovery in diseases like cancer.

Keywords:

mass spectrometry imaging spatial lipidomics spectrum deconvolution tissue heterogeneity

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Area of Science:

Biochemistry
Analytical Chemistry
Molecular Imaging

Background:

Tissue lipid analysis requires high resolution and spatial context.
Conventional mass spectrometry imaging (MSI) limits analytical depth versus spatial resolution.

Purpose of the Study:

Introduce Deconvolution-based Structure-Specific Spatial Lipidomics (DeconS2L) for advanced lipidomics.
Overcome limitations of conventional MSI for comprehensive tissue lipid analysis.

Main Methods:

DeconS2L couples per-pixel and broadband MS/MS sampling with deconvolution algorithms.
Lipids are co-fragmented for convolved MS/MS spectra to improve throughput.
Utilizes tissue heterogeneity for large-scale lipid annotation and imaging.

Main Results:

Analyzed mouse cerebellum tissue, identifying 100 lipids and enabling multiplexed imaging.
Resolved isobaric interferences in human hepatocellular carcinoma (HCC) tissues.
Revealed tumor-specific enrichment of PC 33:1 and triglyceride saturation heterogeneity in HCC.

Conclusions:

DeconS2L integrates molecular annotation with spatial lipidomics.
Demonstrates potential for in-depth biomarker discovery in clinical pathology.
Offers a versatile methodology for complex biological samples.